Achieving sustainable cultivation of tomatoes

Achieving sustainable cultivation of tomatoes

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BURLEIGH DODDS SERIES IN AGRICULTURAL SCIENCE

NUMBER 07

Achieving sustainable cultivation of tomatoesEdited by Dr Autar K. Mattoo, USDA-ARS, USA and Professor Avtar K. Handa, Purdue University, USA

Published by Burleigh Dodds Science Publishing Limited82 High Street, Sawston, Cambridge CB22 3HJ, UKwww.bdspublishing.com

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ContentsSeries list xi

Acknowledgements xv

Preface xvi

Introduction xviii

Part 1 Cultivation techniques

1 Modelling crop growth and yield in tomato cultivation 3Kenneth J. Boote, University of Florida, USA

1 Introduction 32 Review of tomato crop modelling and introduction of the

CROPGRO-Tomato model 43 Important processes and temperature sensitivities in the

CROPGRO-Tomato model 54 Integrating temperature effects and simulating growth and

yield for tomato crops 105 Water and nitrogen balance in the CROPGRO-Tomato model 126 Illustrating growth dynamics of the CROPGRO-Tomato model

and evaluations against field data 137 Simulating tomato growth and yield response under N-limited and

water-limited conditions 158 Summary 179 Future trends in research 18

10 Where to look for further information 1911 References 19

2 Optimizing yields in tomato cultivation: maximizing tomato plant use of resources 23V. S. Almeida, F. T. Delazari, C. Nick, W. L. Araújo and D. J. H. Silva, Universidade Federal de Viçosa, Brazil

1 Introduction 232 Factors affecting stomatal opening in tomato plants 253 Interaction of stomatal opening factors 314 Cultivation practices to maximize tomato plant use of resources 325 Evaluation of plant water status 346 Future trends and conclusion 357 Acknowledgements 358 References 35

3 Improving water and nutrient management in tomato cultivation 41E. Simonne, M. Ozores-Hampton, A. Simonne and A. Gazula, University of Florida, USA

1 Introduction 412 Overview of tomato production systems 42

vi Contents


3 Environmental regulations affecting tomato production in the United States 434 Changing approaches to water and nutrient management:

from optimizing production to optimizing input efficiency 455 Irrigation management systems for tomato production 476 Optimizing irrigation volumes and scheduling 497 Fertilization in tomato production: introduction and soil sampling 548 Nutrient sources for tomato production 569 Optimizing nitrogen (N) rates 59

10 Fertilizer recommendations, nutrient uptake and leaching 6111 Implications of water and fertilizer use for food safety 6312 Teaching water and nutrient management to tomato producers 6413 Future trends and conclusion 6614 Where to look for further information 6615 References 67

4 Organic greenhouse tomato production 77Martine Dorais, Agriculture and Agri-Food Canada, Laval University, Quebec, Canada

1 Introduction 772 Principles and standards of organic greenhouse cultivation 783 Expansion of organic protected tomato cultivation around the world 794 Types of greenhouses used for organic tomato cultivation around the world 805 Productivity and profitability of organic greenhouse tomato production 826 Cultivar and rootstock selection and seedling production 847 Organic greenhouse production systems 858 Fertilisation management 929 Water management 98

10 Plant protection 9911 Health and nutritive value 10112 Environmental impact of organic greenhouse tomatoes 10313 Future trends and conclusion 10414 Where to look for further information 10615 References 106

Part 2 Plant physiology and breeding

5 Understanding and improving water-use efficiency and drought resistance in tomato 117A. Zsögön, Universidade Federal de Viçosa, Brazil; and M. H. Vicente, D. S. Reartes and L. E. P. Peres, Universidade de São Paulo, Brazil

1 Introduction 1172 Tomato as a genetic model in plant biology 1183 Patterns in tomato plant development 1194 Water relations in tomato 1235 Natural genetic variation in tomato 1256 Case study: Solanum pennellii as a source of drought-resistance 1277 Plant development and water relations 1298 Future trends and conclusion 130


Contents vii


6 Ensuring the genetic diversity of tomato 143Andreas W. Ebert and Lawrence Kenyon, AVRDC – The World Vegetable Center, Taiwan

1 Introduction: key issues relating to the genetic diversity of tomatoes 1432 Taxonomy and mating system of tomato and its wild relatives 1453 Conservation of tomato genetic resources worldwide 1474 Policies affecting access to plant genetic resources 1525 Issues affecting the exchange and use of plant genetic resources 1536 Phytosanitary requirements for the exchange of plant genetic resources 1557 Phytosanitary measures in practice: the case of solanaceous viroids 1568 Ways to strengthen sharing of crop genetic resources 1599 Summary and future trends 161


7 Tomato plant responses to biotic and abiotic stress 169C. A. Avila, S. C. Irigoyen and K. K. Mandadi, Texas A&M AgriLife Research, USA

1 Introduction 1692 Tomato responses to biotic stress 1703 Tomato responses to abiotic stresses 1724 Stress signalling and stress regulatory networks 1745 Future trends 1756 Where to look for further information 1777 Acknowledgements 1798 References 179

8 Developments in tomato breeding: conventional and biotechnology tools 187Y. Bai, Wageningen University and Research, The Netherlands

1 Introduction 1872 Tomato domestication and breeding 1883 Conventional tools in tomato introgression breeding 1904 Mutagenesis and tomato mutant libraries 1935 Future trends 1966 Where to look for further information 1977 Conclusion 1978 Acknowledgements 1989 References 198

9 Advances in marker-assisted breeding of tomatoes 203Junming Li, Institute of Vegetables and Flowers – Chinese Academy of Agricultural Sciences (CAAS), China

1 Introduction 2032 Marker development 2053 Populations for mapping 2064 Strategies for trait association and GWAS 207

viii Contents


5 Mapping targeted traits in tomato 2086 Selection methods 2157 MAS progress in tomato breeding 2178 Current developments in tomato breeding 2189 Conclusions and future trends 221


10 Genetic engineering of tomato to improve nutritional quality, resistance to abiotic and biotic stresses, and for non-food applications 239B. Kaur and A. K. Handa, Purdue University, USA; and A. K. Mattoo, USDA-ARS, USA

1 Introduction 2392 History of tomato transformation and challenges 2413 Genetic engineering of tomato for fruit quality and shelf life 2424 Abiotic stress tolerance 2525 Biotic stress tolerance 2596 Tomato as a model system for biopharming 2637 Future trends and conclusion 2648 Where to look for further information 2659 Acknowledgements 266

10 References 266

11 Developing tomato varieties with improved flavour 283M. Causse, E. Albert and C. Sauvage, INRA, France

1 Introduction 2832 Genetic diversity of tomato flavour and consumer expectations 2843 Genes and quantitative trait loci affecting flavour 2864 Tomato texture 2925 New approaches to tomato flavour diversity and genetic control 2936 From MAS to genomic selection for flavour breeding 2957 Interactions genotype by environment: a tool for breeding good tomatoes 2978 Future trends 2999 Conclusion 300


12 Understanding and improving the shelf life of tomatoes 315K. Wang and A. K. Handa, Purdue University, USA; and A. K. Mattoo, USDA-ARS, USA

1 Introduction 3152 Natural variability 3173 Ripening mutants 3184 Molecular determinants 3195 Role of cell wall proteins 3206 Role of epidermal waxes 3217 Hormonal regulation 3228 Controlling pathogen-based impairments 3259 Pre-harvest strategies 326


Contents ix

10 Post-harvest chemical application 32811 Post-harvest management 32912 Conclusion and future trends 33013 Where to look for further information 33114 Acknowledgements 33115 References 331

Part 3 Diseases, pests and weeds

13 Insect-transmitted viral diseases infecting tomato crops 345H. Czosnek, Hebrew University of Jerusalem, Israel; A. Koren, Hishtil Nursery, Israel; and F. Vidavski, Tomatech R&D, Israel

1 Introduction 3452 Viruses transmitted by aphids 3463 Transmission by thrips: tomato spotted wilt virus 3504 Transmission of Begomoviruses by the tobacco whitefly (Bemisia tabaci) 3535 Transmission of RNA viruses by whiteflies 3576 Viruses spread by leafhoppers 3597 Genetics tools to control viral infestation of tomatoes 3608 Future trends and conclusion 3689 Where to look for further information 369

10 References 369

14 Genetic resistance to viruses in tomato 381Moshe Lapidot and Ilan Levin, Institute of Plant Sciences – Volcani Center, ARO, Israel

1 Introduction 3812 Case study 1: Resistance to TYLCV 3823 Case Study 2: Resistance to Tobamoviruses 3864 Case study 3: Resistance to TSWV 3895 Summary and future trends 3916 Acknowledgements 3927 Where to look for further information 3928 References 393

15 Bio-ecology of major insect and mite pests of tomato crops in the tropics 401R. Srinivasan, AVRDC – The World Vegetable Center, Taiwan

1 Introduction 4012 Aphids 4023 Thrips 4034 Whitefly 4045 Leaf miner 4076 South American tomato leaf miner 4087 Tomato fruit borer 4108 Armyworms 4119 Spider mites 414

10 Conclusions 41511 Where to look for further information 41612 References 416

x Contents


16 Integrated pest management in tomato cultivation 421Robert L. Gilbertson, Marcela Vasquez-Mayorga and Mônica Macedo, University of California-Davis, USA; and R. Muniappan, Virginia Tech, USA

1 Introduction 4212 Integrated pest management (IPM): overview 4243 IPM techniques before the growing season 4274 IPM techniques during the growing season 4345 Technologies targeting pests that can be used before

and during the growing season 4376 IPM techniques after the growing season 4397 Diagnostics and monitoring for diseases 4418 Conclusion and future trends 4449 Acknowledgement 445

10 References 446

17 Developing disease-resistant tomato varieties 449D. R. Panthee, J. P. Kressin and P. Adhikari, North Carolina State University, USA

1 Introduction 4492 Bacterial disease resistance breeding 4513 Fungal disease resistance breeding 4644 Virus disease resistance breeding 4695 Nematode resistance breeding 4726 Genetic engineering for developing disease-resistant tomatoes 4747 Where to look for further information 4768 Future trends and conclusion 4769 References 477

18 Integrated weed management in tomato cultivation 495Francesco Tei and Euro Pannacci, University of Perugia, Italy

1 Introduction 4952 Weed communities: the target 4963 The effect of weed–crop interference 5014 Integrated weed management (IWM) 5025 Preventative measures and cultural control: crop rotation and cover crops 5036 Cultural control: stale seedbed preparation, cultivar selection, planting,

irrigation and fertilization 5057 Decision making: weed competition thresholds 5068 Direct weed control methods: mulches, solarization, thermal

and mechanical methods and hand weeding 5089 Chemical weed control 512

10 Case studies 51311 Summary and future trends 51612 Where to look for further information 51813 References 519

Index 533


Series listTitle Series number

Achieving sustainable cultivation of maize - Vol 1 001From improved varieties to local applications Edited by: Dr Dave Watson, CGIAR Maize Research Program Manager, CIMMYT, Mexico

Achieving sustainable cultivation of maize - Vol 2 002Cultivation techniques, pest and disease control Edited by: Dr Dave Watson, CGIAR Maize Research Program Manager, CIMMYT, Mexico

Achieving sustainable cultivation of rice - Vol 1 003Breeding for higher yield and quality Edited by: Prof. Takuji Sasaki, Tokyo University of Agriculture, Japan

Achieving sustainable cultivation of rice - Vol 2 004Cultivation, pest and disease managementEdited by: Prof. Takuji Sasaki, Tokyo University of Agriculture, Japan

Achieving sustainable cultivation of wheat - Vol 1 005Breeding, quality traits, pests and diseasesEdited by: Prof. Peter Langridge, The University of Adelaide, Australia

Achieving sustainable cultivation of wheat - Vol 2 006Cultivation techniquesEdited by: Prof. Peter Langridge, The University of Adelaide, Australia

Achieving sustainable cultivation of tomatoes 007Edited by: Dr Autar Mattoo, USDA-ARS, USA & Prof. Avtar Handa, Purdue University, USA

Achieving sustainable production of milk - Vol 1 008Milk composition, genetics and breedingEdited by: Dr Nico van Belzen, International Dairy Federation (IDF), Belgium

Achieving sustainable production of milk - Vol 2 009Safety, quality and sustainabilityEdited by: Dr Nico van Belzen, International Dairy Federation (IDF), Belgium

Achieving sustainable production of milk - Vol 3 010Dairy herd management and welfareEdited by: Prof. John Webster, University of Bristol, UK

Ensuring safety and quality in the production of beef - Vol 1 011SafetyEdited by: Prof. Gary Acuff, Texas A&M University, USA & Prof.James Dickson, Iowa State University, USA

Ensuring safety and quality in the production of beef - Vol 2 012QualityEdited by: Prof. Michael Dikeman, Kansas State University, USA

Achieving sustainable production of poultry meat - Vol 1 013Safety, quality and sustainabilityEdited by: Prof. Steven C. Ricke, University of Arkansas, USA

Achieving sustainable production of poultry meat - Vol 2 014Breeding and nutritionEdited by: Prof. Todd Applegate, University of Georgia, USA

Achieving sustainable production of poultry meat - Vol 3 015Health and welfareEdited by: Prof. Todd Applegate, University of Georgia, USA

xii Series list


Achieving sustainable production of eggs - Vol 1 016Safety and qualityEdited by: Prof. Julie Roberts, University of New England, Australia

Achieving sustainable production of eggs - Vol 2 017Animal welfare and sustainabilityEdited by: Prof. Julie Roberts, University of New England, Australia

Achieving sustainable cultivation of apples 018Edited by: Dr Kate Evans, Washington State University, USA

Integrated disease management of wheat and barley 019Edited by: Prof. Richard Oliver, Curtin University, Australia

Achieving sustainable cultivation of cassava - Vol 1 020Cultivation techniquesEdited by: Dr Clair Hershey, formerly International Center for Tropical Agriculture (CIAT), Colombia

Achieving sustainable cultivation of cassava - Vol 2 021Genetics, breeding, pests and diseasesEdited by: Dr Clair Hershey, formerly International Center for Tropical Agriculture (CIAT), Colombia

Achieving sustainable production of sheep 022Edited by: Prof. Johan Greyling, University of the Free State, South Africa

Achieving sustainable production of pig meat - Vol 1 023Safety, quality and sustainabilityEdited by: Prof. Alan Mathew, Purdue University, USA

Achieving sustainable production of pig meat - Vol 2 024Animal breeding and nutritionEdited by: Prof. Julian Wiseman, University of Nottingham, UK

Achieving sustainable production of pig meat - Vol 3 025Animal health and welfareEdited by: Prof. Julian Wiseman, University of Nottingham, UK

Achieving sustainable cultivation of potatoes - Vol 1 026Breeding, nutritional and sensory qualityEdited by: Prof. Gefu Wang-Pruski, Dalhousie University, Canada

Achieving sustainable cultivation of oil palm - Vol 1 027Introduction, breeding and cultivation techniquesEdited by: Prof. Alain Rival, Center for International Cooperation in Agricultural Research for Development (CIRAD), France

Achieving sustainable cultivation of oil palm - Vol 2 028Diseases, pests, quality and sustainabilityEdited by: Prof. Alain Rival, Center for International Cooperation in Agricultural Research for Development (CIRAD), France

Achieving sustainable cultivation of soybeans - Vol 1 029Breeding and cultivation techniquesEdited by: Prof. Henry Nguyen, University of Missouri, USA

Achieving sustainable cultivation of soybeans - Vol 2 030Diseases, pests, food and non-food usesEdited by: Prof. Henry Nguyen, University of Missouri, USA

Achieving sustainable cultivation of sorghum - Vol 1 031Genetics, breeding and production techniquesEdited by: Prof. Bill Rooney, Texas A&M University, USA


Series list xiii

Achieving sustainable cultivation of sorghum - Vol 2 032Sorghum utilisation around the worldEdited by: Prof. Bill Rooney, Texas A&M University, USA

Achieving sustainable cultivation of potatoes - Vol 2 033Production and storage, crop protection and sustainabilityEdited by: Dr Stuart Wale, Potato Dynamics Ltd, UK

Achieving sustainable cultivation of mangoes 034Edited by: Professor Víctor Galán Saúco, Instituto Canario de Investigaciones Agrarias (ICIA), Spain & Dr Ping Lu, Charles Darwin University, Australia

Achieving sustainable cultivation of grain legumes - Vol 1 035Advances in breeding and cultivation techniquesEdited by: Dr Shoba Sivasankar et al., CGIAR Research Program on Grain Legumes, ICRISAT, India

Achieving sustainable cultivation of grain legumes - Vol 2 036Improving cultivation of particular grain legumesEdited by: Dr Shoba Sivasankar et al., CGIAR Research Program on Grain Legumes, ICRISAT, India

Achieving sustainable cultivation of sugarcane - Vol 1 037Cultivation techniques, quality and sustainabilityEdited by: Prof. Philippe Rott, University of Florida, USA

Achieving sustainable cultivation of sugarcane - Vol 2 038Breeding, pests and diseasesEdited by: Prof. Philippe Rott, University of Florida, USA

Achieving sustainable cultivation of coffee 039Breeding and quality traitsEdited by: Dr Philippe Lashermes, Institut de Recherche pour le Développement (IRD), France

Achieving sustainable cultivation of bananas - Vol 1 040Cultivation techniquesEdited by: Prof. Gert Kema, Wageningen University, The Netherlands & Prof. André Drenth, University of Queensland, Australia

Global Tea Science 041Current status and future needsEdited by: Dr V. S. Sharma, Formerly UPASI Tea Research Institute, India & Dr M. T. Kumudini Gunasekare, Coordinating Secretariat for Science Technology and Innovation (COSTI), Sri Lanka

Integrated weed management 042Edited by: Emeritus Prof. Rob Zimdahl, Colorado State University, USA

Achieving sustainable cultivation of cocoa - Vol 1 043Genetics, breeding, cultivation and qualityEdited by: Prof. Pathmanathan Umaharan, Cocoa Research Centre – The University of the West Indies, Trinidad and Tobago

Achieving sustainable cultivation of cocoa - Vol 2 044Diseases, pests and sustainabilityEdited by: Prof. Pathmanathan Umaharan, Cocoa Research Centre – The University of the West Indies, Trinidad and Tobago

Water management for sustainable agriculture 045Edited by: Prof. Theib Oweis, Formerly ICARDA, Lebanon

Improving organic animal farming 046Edited by: Dr Mette Vaarst, Aarhus University, Denmark & Dr Stephen Roderick, Duchy College, Cornwall, UK

Improving organic crop cultivation 047Edited by: Prof. Ulrich Köpke, University of Bonn, Germany

xiv Series list


Managing soil health for sustainable agriculture - Vol 1 048FundamentalsEdited by: Dr Don Reicosky, USDA-ARS, USA

Managing soil health for sustainable agriculture - Vol 2 049Monitoring and managementEdited by: Dr Don Reicosky, USDA-ARS, USA

Rice insect pests and their management 050E. A. Heinrichs, Francis E. Nwilene, Michael J. Stout, Buyung A. R. Hadi & Thais Freitas

Improving grassland and pasture management in temperate agriculture 051Edited by: Prof. Athole Marshall & Dr Rosemary Collins, University of Aberystwyth, UK

Precision agriculture for sustainability 052Edited by: Dr John Stafford, Silsoe Solutions, UK


AcknowledgementsWe wish to acknowledge the following for their help in reviewing particular chapters:

– Chapter 10: Dr Tiziana Pandolfini, University of Verona, Italy

– Chapter 12: Dr Yang Zhang, Sichuan University, China/formerly John Innes Centre, UK


PrefaceTomato is the second largest horticultural crop after potato, a worldwide industry valued at over $50 billion. In addition to being a cash crop for farmers, tomato fruit is a significant dietary source of micronutrients, vitamins and antioxidants in maintaining and enhancing human health. It is important to consumers both as a product bought fresh and as a raw material in many processed foods.

As a horticultural crop, production cost per acre is high and profitable production is dependent on a large number of factors. In addition to the right cultivation methods, high-yielding tomato crops also require consistent pre- and post-harvest pest control, as well as appropriate post-harvest handling and effective storage. In the past few decades there has also been an increased emphasis on greenhouse production, greater sustainability and organic production.

High tomato yields also depend greatly on the development of improved cultivars with desirable fruit quality attributes and other agronomic traits such as water and nutrient use efficiency and the ability to cope with biotic and abiotic stresses. The emphasis on a stronger scientific foundation for adding desirable traits for crop production and tolerance to extreme environments has merged plant physiology and molecular breeding disciplines. The need of consumers for healthier products with potential nutraceutical properties has also encouraged improved breeding techniques and genetic engineering strategies including genome editing to further improve fruit quality attributes.

The need for a comprehensive treatise reviewing these important trends in research, with contributions by distinguished experts in their fields, is met by this book with chapters dealing with cultivation techniques in the field and in the greenhouse, together with molecular breeding and genetic engineering technologies for improving nutritional quality, flavour and shelf life, as well as weed and pest management including managing insects, viruses and other pathogens. Of particular importance is the emphasis on the sustainability of tomato productions in various parts of the world.

Part 1 has four chapters dedicated to cultivation practices including crop growth and yield modelling, good agricultural practices in tomato production, management of water and nutrient use efficiency, and sustainable and greenhouse tomato production. Part 2 has eight chapters discussing advances in understanding tomato plant physiology, maintaining tomato genetic diversity, responses to biotic and abiotic stresses, conventional tomato breeding, marker-assisted breeding, genetic engineering using molecular tools, improving flavour and desirability, and enhancing fruit shelf life. Part 3 has six chapters that focus on disease, pest and weeds during tomato cultivation and production, in particular, insect-transmitted diseases, the genetic basis of resistance to viruses, insect pests and integrated pest management, advances in developing pathogen-resistant tomato varieties, advances in insect resistance and integrated weed management during tomato cultivation.

The world today faces major challenges that include global climate change and the projected increase in human population to 10 billion by 2050. We are already witnessing serious pressures on water and other natural resources, particularly in developing countries. In some countries, there are already instances of using unclean water, even sewage water, for tomato production and post-harvest operations, seriously contributing to human health problems. To overcome these challenges in crop production, including tomato cultivation, there is more and more need for sustainable agricultural practices to achieve both higher


Preface xvii

yields and safe, high-quality foods. The chapters in this book are designed to help achieve this goal. We sincerely thank all the authors for their outstanding contributions and the staff at BDS Publishing for diligently working with us to bring forth this volume in a timely manner. This book on tomato should prove an important reference source for researchers, students, growers and practitioners of sustainable agriculture.

Autar K. MattooUSDA-ARS,

The Henry A Wallace Beltsville Agricultural Research Center,Beltsville, MD 20705-2350, USA

([email protected])

Avtar K. HandaDepartment of Horticulture and Landscape Architecture,

Purdue University,West Lafayette, IN 47907-2010, USA

([email protected])

usda.gov


IntroductionTomato (Solanum lycopersicum L.) is the world’s second largest horticultural crop after potato, with production valued at over $50 billion. In the last twenty years, production has doubled to over 160 million metric tons. In addition to being a cash crop for farmers, tomato fruit is a significant dietary source of micronutrients, vitamins and antioxidants in maintaining and enhancing human health. It is important to consumers both as a product bought fresh and as a raw material in many processed foods.

As stated in the Preface, tomato cultivation, like other crops, faces a range of challenges. There is increasing competition for water, land, labour and other resources, requiring more efficient cultivation with fewer inputs. Cultivation must mitigate its impact on the environment which contributes to climate change whilst adapting to potentially more extreme weather associated with global warming. It must also deal with continuing pressure from insect pests and diseases. Finally, higher yields must be compatible with qualities such as flavour, shelf life and nutritional value (including preserving and enhancing the important nutraceutical properties of tomatoes). Achieving sustainable cultivation of tomatoes summarises key research addressing these challenges. This Introduction provides a more detailed review of the topics covered in each chapter.

Part 1 Cultivation techniques

Optimising inputs and improving yields needs benchmarks against which performance can be assessed. Crop growth simulation models have become important tools for researchers and growers in optimising production. Chapter 1 reviews existing models used for tomato cultivation, their strengths and weaknesses, before focusing on the CROPGRO-Tomato model. Through successive refinements, this model is able to simulate crop development, the effects of temperature and inputs such as nitrogen and water as well as potential yields. The authors show how the CROPGRO-Tomato model can be used by producers to manage their tomato crop in several ways: (1) predicting probable maturity date and yield, (2) optimising irrigation strategies, (3) optimising nitrogen fertiliser use and (4) predicting fruit size. It includes practical examples of the way the model has been used to optimise irrigation and fertiliser use.

Chapter 2 looks at how a better understanding of plant physiology can be used to optimise cultivation practices, focusing on the operation of leaf stomata. The opening and closing of the stomata affect a plant’s photosynthesis, transpiration and respiration, which, in turn, affect plant and fruit development. The chapter reviews factors that affect stomata opening and closure such as soil water availability, light, relative air moisture and temperature. It then reviews cultivation practices such as plant spacing and pruning that support stomatal opening and thus boost yield and fruit quality. Chapter 2 can be read alongside Chapter 5. This chapter discusses how physiological mechanisms such as stomatal opening affect the way tomatoes manage way and how this understanding can then be used to develop more drought-resistant varieties.

Building on this understanding of the way plants manage resources, Chapter 3 reviews best practice in water and nutrient management. It looks at the shift in approach from optimising production to optimising input efficiency. It then discusses how to schedule


Introduction xix

irrigation more effectively to minimise water use. The chapter goes on to review ways of optimising fertiliser use from soil sampling and testing, selection of the right kind of fertiliser, the use of cover crops, compost and manure to ways of determining appropriate nitrogen (N) rates.

Chapter 4 reviews a rapidly expanding sector in tomato production, organic greenhouse tomato cultivation. This production system endeavours to minimise system inputs and adverse environmental impacts through sustainable water and waste management, limited fossil energy use, nutrient-balanced approaches, and mechanical and biological control of pests. The chapter explores how this can be achieved through the use of appropriate types of greenhouse, cultivar and rootstock selection and seedling production; organic greenhouse production systems; fertilisation and water management; and plant protection methods.

Part 2 Plant physiology and breeding

Since tomato is mainly cultivated under irrigated conditions, water use is of considerable significance for healthy plant growth and adequate yield. Indeed, water is the most limiting and yet essential resource needed by plants to grow and function efficiently. Chapter 5 starts by summarising what we know about genetic factors affecting the vegetative growth and flowering as well as the ways tomato plants regulate water intake to manage this growth. This chapter then looks at physiological mechanisms such as root–shoot ratios and the regulation of stomatal opening which affect water use efficiency (WUE) and drought resistance in tomato plants. It also reviews genetic variation in wild varieties such Solanum pennellii related to WUE and drought resistance and the genetic factors affecting desirable traits to optimise water use. Finally, it shows how this understanding can be used to breed more drought-resistant varieties.

The importance of wild varieties and genetic diversity discussed in Chapter 5 is picked up by Chapter 6. The exploitation of genetic diversity to develop crops with greater resistance to both biotic and abiotic stresses, or with enhanced phytonutrient content, is of strategic importance to combat the negative impact of climate change. Today, crop wild relatives that are threatened in the wild, and which are only partially conserved in genebanks, are being rediscovered as essential resources for crop improvement programmes. Accessibility and use of crop wild relatives for crop improvement is especially important in tomatoes, a crop where a cultivated variety contains less than 5% of the genetic diversity of its wild relative. Chapter 6 reviews current global ex situ conservation of tomato germplasm and the use of databases such as Genesys to search genebank collections. The chapter also deals with the policy framework for the conservation, access and benefit sharing mechanisms of plant genetic resources (PGR). It describes how the policy framework and stricter phytosanitary requirements affect the exchange and use of PGR. Ways to strengthen sharing of PGR for food and nutrition security and climate change adaptation are discussed.

Chapter 7 builds on Chapter 6 by showing how we can exploit tomato genetic resources. It also links to Chapters 2 and 5 in showing how we can make use of recent advances in understanding plant physiology. A major challenge in tomato production is to increase productivity by improving resistance and tolerance to crop stresses. Cultivar improvement depends on our ability to identify, study and leverage the genetic diversity present among tomato germplasm resources worldwide from which new resistance/tolerance traits can be selected and transferred via breeding and biotechnology. Chapter 7 summarises the

xx Introduction


current status and advances in our understanding of tomato stress responses in tomato plants, including stress signalling and stress regulatory networks. It also discusses future trends in tomato stress biology and its potential implications for tomato improvement.

Chapter 8 reviews developments in ‘conventional’ breeding, which is defined as the integrated application of classic genetics principles and genomics through visual and/or molecular selection with non-GM (genetic modification) tools. Chapter 8 discusses four conventional methods: true breeding, tomato hybrids, introgression breeding and mutagenesis. True breeding occurs mainly by selecting preferred genotypes in the existing germplasm, which have arisen from recombination, natural mutations and spontaneous outcrossing with wild relatives. To deal with the narrow genetic diversity in cultivated tomato, new traits from wild germplasm can be introduced into the cultivated tomato through recurrent backcrossing. Introgression of alien genes from wild relatives has played a major role in tomato hybrid breeding, for which molecular tools have been integrated with traditional breeding methods, crossing/backcrossing and visual selection. The chapter reviews ways of dealing with the breeding barriers that arise in interspecific crosses, including unilateral incompatibility, hybrid inviability, sterility and reduced recombination, chromosomal rearrangement and inversion. It also discusses the generation of genetic variation by mutagenesis treatments which have proven to be a powerful method for the unravelling of biological processes and the alteration of agronomical traits in plant species such as tomato. Finally, it reviews recent advances in sequencing technology and gene editing techniques which promise to revolutionise plant breeding.

Chapter 8 provides a foundation for Chapter 9, which describes the process of marker development and how this can be used to improve tomato breeding. Marker-assisted selection (MAS) makes selection independent of the phenotypic expression of the traits and enables fast, precise introgression of these desired traits. The chapter reviews marker development, populations for mapping, strategies for trait association and genome-wide association studies, mapping targeted traits in tomato (such as disease resistance, abiotic stress tolerance, fruit quality and yield-quality traits) and how they support MAS techniques such as marker-assisted backcrossing (MABC) and marker-assisted recurrent selection as well as genomic selection (GS). The chapter explores the reasons for the gap that still exists between gene/ quantitative trait loci (QTL) mapping and the implementation of MAS, and problems such as the need for better characterisation of available genetic resources, and suggests how the technique can be developed further.

Chapter 10 shows how genetic dissection using fruit ripening mutants, new transgenic plants and molecular breeding has created a road map for the further unravelling of the regulation of genes governing fruit quality attributes and fundamental metabolic processes. Precision in engineering plant genomes has enabled development of novel tomatoes with marketable traits such as enhanced quality and shelf life, abiotic and biotic stress tolerance as well as for non-food applications such as production of oral vaccines.

Tomato fruit quality is a complex trait involving a number of components including appearance, flavour, aroma and texture. A few major genetic mutations have been found to have a significant effect on fruit quality (notably the rin mutation). Chapter 11 examines the use of QTL mapping to identify favourable sensory characteristics such as flavour, exploring current technologies and suggesting future trends for research in this area. New approaches such as genome-wide association studies or MAGIC populations using genome information are allowing a higher precision of QTL location. The chapter looks at progress in moving from MAS to GS for flavour breeding.


Introduction xxi

The shelf life of tomatoes is regulated via myriad physiological, biochemical and environmental processes, including hormonal regulation and the activity of cell wall proteins. As Chapter 12 shows, ripening is associated with marked changes in gene expression, regulating the biosynthesis of a large number of catabolic enzymes, including cell wall hydrolases implicated in fruit softening. The chapter explores the advantages and disadvantages of cultivating ripening-impaired tomato mutants and genetically engineered genotypes characterised by inhibition of the ripening process.

Part 3 Diseases, pests and weeds

As Chapter 13 describes, many viruses transmitted by insects cause great damage to tomato crops in the field and in the greenhouse. It has been estimated that pests and diseases contribute to about 40% of tomato yield loss in the field worldwide. Management of insect-transmitted tomato viruses is a race between the emergence of new viruses coupled with the proliferation of quickly adapting vectors and strategies that include physical and chemical protection from insects and development of virus-tolerant crops. The major insect-transmitted viruses infecting tomato are described in detail in this chapter, including viruses transmitted by aphids, thrips, whitefly and leafhoppers such as tomato spotted wilt virus, tomato yellow leaf curl virus, begomoviruses and RNA viruses. The chapter explores the potential of technologies such as genetic engineering to combat insect-transmitted viruses.

As Chapter 14 shows, genetic resistance requires the identification of resistance loci, typically in wild species. The advances made in recent years in the high-throughput sequencing and re-sequencing of whole-plant genomes have made the task of gene identification much easier, enabling fast identification of genes that control resistance and the development of recombination-free precision DNA markers. These whole-plant genome technologies are also invaluable in capturing elite susceptible recipient genomes during backcross breeding programmes designed to introgress genes of interest, including disease resistance genes (GS). These technologies will cumulatively enhance the pyramiding of genes into elite commercial hybrids. The advances made in recent years in genome editing technologies such as CRISPR-Cas are expected to accelerate the breeding of cultivars resistant to diseases such as fungal blights, bacterial spots, bacterial wilts, begomovirus and diseases caused by tospoviruses.

As shown in Chapter 13, tomato production in tropical countries, in particular, is severely constrained by insect and mite pests. As an example, the onset of whitefly early in the season can lead to complete crop loss because of its ability to transmit begomoviruses whilst fruit borers are a serious problem during the reproductive phase of the crop. The use of broad-spectrum chemical pesticides can make this problem worse, as it can encourage the build-up of resistance whilst damaging the natural enemies of these pests. Understanding the bioecology of these pests is therefore essential to developing effective strategies to manage them. Chapter 15 reviews recent research on the bioecology of the major insect and mite pests affecting tomato crops, including aphids, thrips, whitefly, leaf miners, fruit borers, armyworms and spider mites. In each case, the chapter considers pest ecology and how the pest affects the tomato plant. As the chapter shows, there are several natural enemies and disease-causing pathogens attacking these pests. It is possible to exploit species-specific natural enemies and entomopathogens, and integrate them with other components of integrated pest management (IPM) such as resistant cultivars and pheromones.

xxii Introduction


Understanding the ecology of insect pests is the foundation for the development of successful IPM strategies for dealing with them. This is the subject of Chapter 16, which reviews key aspects of IPM before, during and after the growing season, from the use of high-quality pest and pathogen-free seeds and transplants and effective monitoring systems to post-harvest sanitation techniques. The chapter demonstrates the considerable progress that has been made in the development and implementation of IPM packages for tomato production including improved diagnosis, an increase in the tactics available for inclusion in packages and development of packages for different production systems. A continuing challenge will be to develop effective IPM packages for smallholder farmers in tropical and subtropical regions where overlapping crops are grown throughout the year. It is in these situations where excessive pesticide use is most common and the potential for benefits from IPM programmes are the greatest.

As noted earlier, tomato is known to be afflicted by at least 200 different disease-causing organisms from most major pathogen classes – bacteria, fungi (including Oomycota), viruses and nematodes. Despite decades of conventional breeding and selection, there are still a large number of diseases caused by these pathogen classes that make tomato production challenging in various parts of the world. Current advances in tomato genetics and genomics can be combined with conventional plant breeding methods to introgress resistance genes and expedite the breeding process. Building on Chapter 14, Chapter 17 summarises current advances in the development of disease-resistant varieties. The chapter provides a systematic review of progress in tackling particular tomato diseases caused by bacteria, fungi, viruses and nematodes, showing that, with the incorporation of MAS, the rate of improvement has been significantly enhanced, even if many challenges remain.

Weeds have long been recognised as a source of considerable economic loss in agriculture. Weeds not only cause crop yield losses due to competition for resources but may also host pests and pathogens that can be detrimental to the crop. Chapter 18 reviews best practices in integrated weed management (IWM) which combines the use of indirect (i.e. preventive measures and agronomic practices) and direct (i.e. physical, mechanical, biological and chemical methods) weed control strategies. The chapter discusses topics such as competition thresholds, cultural control techniques from stale seedbeds to crop rotations, cover crops and mulches, physical control methods such as solarisation, thermal and mechanical weeding, and the continuing role for chemical treatments.

Summary

The chapters in Achieving sustainable cultivation of tomatoes highlight a number of key themes in tomato research. These include how a greater understanding of plant physiology is informing improvements in both cultivation and breeding (Chapters 2, 5 and 7). A second theme is the critical importance of wild varieties (Chapters 5–7); the ways that breeding techniques are seeking to capitalise on this rich genetic resource (Chapters 8–10) to improve traits such as flavour, shelf life, drought and disease resistance (Chapters 7, 11, 12, 14 and 17); and the continuing challenges in fully tapping this potential. At the same time, improved varieties still need good cultivation techniques as well as effective IPM and IWM strategies (Chapters 1–4, 16 and 18), which themselves need to build on a deeper understanding of pest biology and ecology (Chapters 13 and 15).

Part 1

Cultivation techniques

http://dx.doi.org/10.19103/AS.2016.0007.16© Burleigh Dodds Science Publishing Limited, 2017. All rights reserved.

Chapter 1

Modelling crop growth and yield in tomato cultivationKenneth J. Boote, University of Florida, USA

1 Introduction

2 Review of tomato crop modelling and introduction of the CROPGRO-Tomato model

3 Important processes and temperature sensitivities in the CROPGRO-Tomato model

4 Integrating temperature effects and simulating growth and yield for tomato crops

5 Water and nitrogen balance in the CROPGRO-Tomato model

6 Illustrating growth dynamics of the CROPGRO-Tomato model and evaluations against field data

7 Simulating tomato growth and yield response under N-limited and water-limited conditions

8 Summary

9 Future trends in research

10 Where to look for further information

11 References

1 Introduction

Crop-growth simulation models have become important tools for researchers and growers for the purpose of assisting management and improving production. The CROPGRO-Tomato model described in this chapter is one of a suite of models within the modelling package Decision Support System for Agrotechnology Transfer (DSSAT), which is widely used and accepted by agricultural research communities (Jones et al., 2003). This model is mechanistic and process oriented (processes of carbon, water and N balance), and it simulates daily progress towards flowering and fruit set as well as daily growth of leaves, stems, roots and fruits over time until maturity or final harvest (Scholberg et al., 1997; Boote et al., 1998; Boote et al., 2012). This chapter describes the model, its sensitivity to climatic and management factors, what it is capable of predicting and how it can be used in various applications of tomato (Solanum lycopersicum Mill.) cultivation in order to address the challenges confronting industry and researchers.

4 Modelling crop growth and yield in tomato cultivation


2 Review of tomato crop modelling and introduction of the CROPGRO-Tomato model

2.1 Brief review of tomato crop modelling and some challengesA number of prior efforts directed towards tomato growth modelling are reviewed here. Many of those models (Jones et al., 1991; Dayan et al., 1993; Heuvelink, 1995, 1996; Marcelis et al., 1998) are designed for single-stem indeterminate growth of tomato in greenhouse conditions, and generally simulate growth and yield under full nitrogen nutrition. (The models do not address N stress or P stress.) TOMGRO is a relatively simple single-stem indeterminate tomato model developed by Jones et al. (1991) that predicts growth of successive leaves and successive fruit trusses and fruit production under non-limiting N conditions in greenhouse. The tomato models developed by Heuvelink (1995, 1996) and Marcelis et al. (1998) are more detailed and mechanistic compared to the TOMGRO model; they are designed for predicting the growth and yield of indeterminate greenhouse-produced tomato. Their models are quite mechanistic and simulate photosynthesis, respiration and fruit setting and growth using explicit sink strength of fruits and vegetative organs. In some cases, tomato models are included within simulations of greenhouse environment as an entire system, and the combined system is used as a horticultural management and teaching tool (Gary et al., 1997, 1998). The TOMGRO model (Jones et al., 1991; Dayan et al., 1993) and the Tompousse model developed by Abreu et al. (2000) are designed to predict greenhouse-grown tomato. The CROPGRO-Tomato model described in this chapter is designed to predict daily growth and yield of field-grown, semi-determinate tomato under limited water and nutrient conditions in the field. Development of the CROPGRO-Tomato model began in 1996 (Scholberg, 1996; Scholberg et al., 1997), and the model was recently more fully tested and improved for temperature parameterization by Boote et al. (2012). It has been used to evaluate N fertilization and irrigation strategies for tomato in southern Italy (Rinaldi, 2007; Rinaldi et al., 2007).

Challenges for modelling tomato production include (1) accurately simulating life cycle and maturation of fruits and yield responses to temperature, whether field or greenhouse; (2) simulating response to soil water availability for a range of production systems, including open-field and mulch-bed systems; (3) simulating response to fertility (N or P); (4) simulating fresh weight of fruits and fruit size distributions and (5) modelling the genetic variation relative to fruit set, fruit size, maturation and yield. From the prior brief review of models for tomato, it is clear that predicting production in greenhouse environments is important, including control of greenhouse temperature and CO2 environment. In both field and greenhouse production, growers want to know the progress of their crop under the past and projected weather conditions for predicting fruit maturation and harvest for marketing. Fruit size distribution is important for marketing. Future collaboration of crop modellers with tomato breeders can be beneficial, not just to better characterize production in producer fields, but to assist breeders in hypothesizing the benefits of heat-tolerant traits, for example, in stressful environments.

2.2 Description of the CROPGRO-Tomato modelThe CROPGRO model was initially developed for annual grain crops, especially grain legumes (Boote et al., 1998); but being a generic model, it was easily adapted for other


Modelling crop growth and yield in tomato cultivation 5

annual crops, including non-legumes, by turning off the N-fixation aspect and predicting fruit mass rather than seed mass as done in the adaptation by Scholberg et al. (1997) for semi-determinate field-grown tomato. CROPGRO is a generic model that uses one common FORTRAN code for all of its crops, but requires a detailed species file for many parameterizations that include initialization, tissue composition and relationships defining the sensitivity of the crop processes to light, water, temperature and N status (see Boote et al., 1998). The model is generic in the sense that there are no hard-wired parameters or equations inside the code. This allowed Scholberg (1996) to start with a template species file from one of the grain legumes and modify it to predict tomato, including its compositions and sensitivity to environmental factors. This process required careful review of the tomato literature to glean appropriate parameters, along with field experiments, to check the predictions of the model and to calibrate species model parameters for which there is no published literature. There is also a cultivar file and an ecotype file with a lesser number of genotype-specific parameters that describe the tomato life cycle and other traits (e.g. time to first flower, time to maturity, rate of leaf appearance, leaf size, fruit size, rate of fruit addition etc.) for the cultivar being predicted. The adaptation by Scholberg et al. (1997) provided a model that was initially functional, but that version benefitted from several later improvements to allow prediction of fruit fresh weight, fruit size and fruit dry matter concentration (Boote and Scholberg, 2006), with additional improvements resulting from the work of Rybak (2009), who measured time-series growth characteristics of individual tomato fruits from three successive cohorts under differential water and N-fertility conditions. Subsequently, Boote et al. (2012) did a thorough review of the recent tomato literature and completely re-parameterized the sensitivity of photosynthesis, vegetative growth, fruit set and fruit growth aspects to temperature. Current work in progress with Brazilian colleagues is adding sensitivity to P fertility and P fertilization as well as re-parameterizing the model for N-limited conditions. Therefore, after these improvements, the CROPGRO-Tomato model promises to be a robust one adapted for predicting the growth and yield of semi-determinate cultivars under field conditions where water and N- and P-limited conditions prevail.

3 Important processes and temperature sensitivities in the CROPGRO-Tomato model

The CROPGRO-Tomato model is process oriented and mechanistic and simulates the various processes of crop development, crop carbon balance, crop N balance, soil–crop water balance and soil N balance. The model uses a one-day time step, except for hourly time steps for the leaf-to-canopy assimilation module. It requires daily weather inputs (solar radiation, maximum temperature, minimum temperature and rainfall), soil water-holding characteristics, soil N-supplying characteristics, crop cultivar characteristics and management information (transplanting date, row spacing, plant spacing, irrigation and fertilization).

3.1 Crop developmentThe model considers both vegetative and reproductive development as a function of temperature and plant water status, simulating the rate of successive leaf formation



on the main stem and the rate of progress towards reproductive stages (first flower, beginning fruit etc.). Simulated successive node number on the main axis is used to influence leaf area expansion of successive leaves during the first five or so leaves produced and also influences the partitioning of assimilate to leaf, stem and root tissue (using a partitioning look-up as a function of current vegetative node number). The reproductive progression (to anthesis, to first fruit, duration of fruit formation and duration from first fruit to beginning fruit maturity) defines the crop life cycle, as well as affecting the partitioning of assimilate to fruits, rate of fruit addition and duration of fruit growth to maturity. Reproductive progression is primarily affected by temperature, and the model uses cardinal temperatures of base temperature and optimum temperature to compute photothermal days per calendar day, which are summed up and compared to the photothermal day requirements to trigger the next reproductive stage. To account for the dependence of processes on temperature, the CROPGRO-Tomato model uses four-point temperature response functions represented by (1) base temperature (Tb), the temperature below which the rate of the process is zero; (2) Topt1, the lowest temperature at which maximum rate is attained; (3) Topt2, the upper temperature at which maximum rate is sustained and (4) maximum temperature, Tfail, the temperature above which the rate is zero. Temperature functions for nearly all processes in CROPGRO are computed hourly following 24-hour diurnal temperatures simulated from daily Tmax and Tmin; thus the functions for processes are the average over the hourly temperatures. Based on temperature experiments of Adams et al. (2001) and as reviewed in Boote et al. (2012), the CROPGRO-Tomato model uses 7, 22, 28 and 48°C for Tb, Topt1, Topt2 and Tfail, respectively, in the species parameter input file as cardinal temperatures for vegetative development and rate of progress towards anthesis. For progress from anthesis to maturity and for fruit development and maturation, the temperature functions use cardinal temperature values of 5.2, 26, 28 and 48°C for Tb, Topt1, Topt2 and Tfail, respectively. Figure 1 shows the effect of those functions on days to anthesis and days to maturity, where the temperature shown

Figure 1 The simulated effect of temperature functions for reproductive development upon days to anthesis and days to maturity, versus mean daily temperature simulated assuming a 10°C diurnal cycle from maximum to minimum daily temperature.



is the result of a 10°C differential from maximum to minimum daily temperature. The experimental knowledge and confidence of the response above 28°C is low.

3.2 Carbon balance and photosynthesisThe model’s carbon balance considers C inputs from photosynthesis, C losses to respiration and losses to senescence and abscission, as well as the partitioning of assimilate to the different organs (leaves, stems, roots and fruits). The CROPGRO-Tomato model simulates single-leaf photosynthesis scaled up to hedgerow canopy assimilation (Boote and Pickering, 1994), where leaf photosynthesis sensitivity to CO2, light, temperature and leaf N concentration is parameterized from literature information. The leaf photosynthesis module combines an asymptotic exponential equation with a modified Farquhar and von Cammerer (1982) approach. Both the light-saturated leaf assimilation rate (Amax) and the quantum efficiency are then moderated by temperature, CO2 and O2 functions (Boote and Pickering, 1994; Pickering et al., 1995). Leaf photosynthesis is predicted hourly for sunlit- and shaded-leaf classes in the canopy and is multiplied hourly by sunlit leaf area index (LAI) and shaded LAI, and scaled or integrated up to daily gross photosynthesis, following Boote and Pickering (1994). This method of scaling up from leaf-to-canopy assimilation has been shown to predict accurate responses to light, CO2 and LAI for grain legumes (Boote and Pickering, 1994; Alagarswamy et al., 2006) and maize (Lizaso et al., 2005a, b). The cultivar parameter, Amax, light-saturated leaf photosynthesis, is a conservative parameter based on literature reports for tomato (Xu et al., 1997; Barrios-Masias et. al., 2014), and this trait does not vary much across cultivars. The work by Boote et al. (2012) describes parameterization of the temperature-dependent processes of light-saturated leaf photosynthesis for the model. The Tb, Topt1, Topt2 and Tfail, respectively, for hourly temperature effect on light-saturated, CO2-saturated leaf photosynthesis is 6, 26, 34 and 48°C, respectively. These instantaneous temperature optimums agree with values reported by Heuvelink and Dorais (2005). There is also a minimum night temperature effect on the model that reduces the next day’s leaf photosynthesis, which concurs with reported reductions in photosynthesis of tomato when the Tmin (night temperature) is below 10°C (Martin et al., 1981; Byrd et al., 1995). An asymptotic function reduces leaf photosynthesis beginning at Tmin of 15°C, going to zero rate at Tmin of 2°C. The Tb and Topt values were, in part, based on literature as well as calibration and optimization against dry matter accumulation in cool versus warm seasons in Florida (Boote et al., 2012). The model accounts for both growth respiration and maintenance respiration. The growth respiration approach follows that of Penning de Vries et al. (1974), in which the cost of synthesizing tissue depends on the approximate composition (carbohydrate, protein, lipid, lignin, organic acid and mineral) of each organ and the biochemical pathways to synthesize those broad classes of compounds. The tomato model species file contains the compositions for plant organs (leaf, stem, root, fruit and seed), as well as the costs given by Penning de Vries and van Laar (1982). In addition, the model considers daily maintenance respiration as a combined function based on total crop mass and daily gross photosynthesis. Maintenance respiration is sensitive to temperature, but growth respiration efficiency is not temperature sensitive. Modelled leaf area expansion (via specific leaf area of new leaves) also has temperature dependency, being reduced at very low or very high temperature. An important point not mentioned is that the CROPGRO model handles transplants of tomato as a way of initializing the model, where the size of the transplant, as well as an estimate of prior seedling growth temperature conditions, is needed.



3.3 Carbon balance and setting of fruitsThe model is source driven, in which the amount of daily assimilate determines the growth of leaves (including leaf area), stems, roots and fruits. Before rapid fruit growth, the partitioning among organs varies with the vegetative stage (node number on main stem, which is a type of thermal accumulator). Once fruit addition begins, explicit numbers of successive daily fruit cohorts are added (along with explicit sink strengths per fruit). The set fruits have first priority for assimilate over vegetative tissues, and the crop continues to flower and add fruits each day as long as assimilates are available. During this phase, vegetative and root growth will be progressively reduced as more fruits are added, but only up to a carrying capacity called XFRUIT. XFRUIT is a cultivar trait that specifies the maximum fraction of assimilate that can be allocated to fruits at the final point of fruit addition. This value can be 0.70 to 0.80 for typical semi-determinate cultivars, which means that the remaining fraction (1.00 – XFRUIT) is reserved for vegetative growth. This would correspond to the concept of constant vegetative sink strength relative to each successive truss added on plants simulated in the TOMSIM model (Heuvelink, 1996). For true indeterminate cultivars, the practical XFRUIT may be as low as 0.50, created in part by genetics, but also by the practice of pruning to one or two main stems and also pruning and harvesting fruits, so as to sustain growth of the apical vegetative-growing meristems. The model can be simulated as an indeterminate plant by using a low XFRUIT, if desired, with a very long crop cycle, continued fruit set and delayed senescence.

3.4 Fruit cohorts and temperature effects on fruit set and growth per fruit

The CROPGRO model has flower and fruit cohorts, with explicit addition of flowers added each day after the beginning flower date. For each daily cohort, the individual flowers progress to form fruit cohorts after a thermally dependent short phase (called FL-SH in the model). Growth rate per fruit then has a slow phase starting immediately after flower opening, followed by a rapid phase (see Boote et al., 2012 for more complete description of this). The decision to carry or abort each successive fruit depends on a temperature stress function and assimilate availability – the model checks to see if the carrying capacity has been reached relative to demand from all prior fruits, similar to Bertin (1995, 2005) and the sink to source ratio of Marcelis et al. (2004). The CROPGRO-Tomato species file contains a temperature function for fruit addition that mimics elevated temperature effects on flower fertility. Fruit set for each flower–fruit cohort depends on the temperature during the flower to fruit-set phase, and the fraction of fruits set (or aborted) follows an hourly temperature-dependent function described by the range Topt1 to Topt2 (optimum temperature) and Tfail (too hot, zero pollination). The temperature range for fruit setting in tomato is narrow and especially the night temperature is critical. The optimal range reported for fruit setting in tomato is reported to be 18 to 20°C (De Koning, 1994). Fruit set is low at both low and excessively high temperatures. Hot conditions may result in cone splitting, stigma exertion and pollen sterility, and maximal day temperature in excess of 32°C and/or minimal night temperature above 21°C greatly reduce fruit set (Moore and Thomas, 1952; Benedictos and Yavari, 2000). Therefore, the cardinal temperatures of 6, 21, 26 and 33°C were used by Boote et al. (2012) as Tb, Topt1, Topt2 and Tfail, respectively, for fruit setting (fruit addition rate) and pollination (Fig. 2), based considerably on these data and those of Adams et al. (2001), except that Adams et al. did not explore values



for ceiling failure temperature. It is likely that differences exist in the upper thresholds for heat-tolerant versus heat-sensitive tomato cultivars (Lohar and Peat, 1998; Sato et al., 2000). Sato et al. (2002) reported that pollen viability is adversely affected by elevated temperature (32/26°C) occurring during the approximate ten-day period prior to flower opening, during which time the pollen is formed and developed.

The growth rate of individual fruits is dependent on both assimilate supply and temperature following a temperature-dependent parameterization. Fruit growth rate follows a genetic potential rate as modified by temperature, although after a full fruit load is set (plant has reached carrying capacity), the remaining fruits share a deficit if assimilate deficit occurs. This feature works sufficiently well in the model to mimic the significant distribution of fruit sizes, as the early-set fruits have much less competition and are larger than late-set fruits (Bohner and Bangerth, 1988; Rybak, 2009; Rybak et al., 2015). Experiments of Fanwoua et al. (2012) reported an important role of sugar content and timing of assimilate supply on variation in fruit size. For parameterizing temperature effects on fruit growth rate, optimum temperatures of 26°C were reported by Rylsky (1979), whereas Adams et al. (2001) found an optimum regimen of 25/25°C (day/night). Values for base temperature and ceiling temperature for the fruit growth rate are difficult to obtain. In the absence of data on ceiling temperature effects on fruit growth, a Tfail (32°C) for fruit growth rate was assumed close to that of fruit addition and pollination (33°C). In addition, a Tb of 6°C was used to be close to the Tb values used for vegetative, reproductive and fruit-set processes. Thus, cardinal temperatures used in the model for fruit (and seed) growth rate are 6, 22, 25 and 32°C for Tb, Topt1, Topt2 and Tfail, respectively, as shown in Fig. 2 (Boote et al., 2012). In addition, the CROPGRO-Tomato species file includes a function that modifies the partitioning limit to fruit growth (XFRUIT) if temperature is high (reduced above 28°C and falling to zero at 34°C), and this function is an additional contributor to elevated temperature effects on fertility in the model (Boote and Scholberg, 2006).

Figure 2 Shape of parameterization of relative temperature effect on fruit set (addition), individual fruit growth rate and on maximum fraction partitioning allowed to fruits for the CROPGRO-Tomato model.



4 Integrating temperature effects and simulating growth and yield for tomato crops

4.1 Integrated effects of temperature functions on yield, crop mass, fruit numbers and fruit size

The result of these parameterizations of temperature effects on fruit set, fruit growth rate and partitioning to fruits is that simulated tomato fruit set is limited by elevated temperature, fruit numbers are reduced and fruit size is reduced as temperature increases (Fig. 3); total fruit growth and final fruit yield are reduced (Fig. 4). Simulated fruit number is relatively stable as high as 24°C, but is progressively reduced at higher mean temperatures, falling to zero at 33°C, as regulated by the functions shown in Fig. 2. Simulated fruit size declines rather continuously as temperature increases (Fig. 3), caused not only by the temperature effect on the rate of single fruit growth, but also by the temperature effect on the duration of fruit growth, which is longer when the temperature is cooler. The simulated temperature effect on fruit size concurs with the general knowledge of observed temperature effects, but additional testing is needed to evaluate the robustness of the model predictions. A consequence of all these temperature-effect parameterizations as well as on photosynthesis is that simulated crop total biomass and fruit yield are reduced as temperature increases (Fig. 4). The higher final crop biomass simulated at cool temperature is caused by longer cycle duration and not by higher photosynthesis. The higher fruit yield at cool temperature is caused by longer fruit growth duration as well, until above 24°C, at which temperature the model functions begin to affect fruit set, fruit growth rate and partitioning, thus reducing the yield to zero at 33°C. Simulated fruit dry weight harvest index (HI) is about 0.70 at cooler temperatures, but HI begins to be reduced progressively above 24°C, falling to zero at

Figure 3 Simulated fruit number per m2 and fresh weight per fruit, resulting from all temperature parameterizations in the CROPGRO-Tomato model, assuming a 10°C diurnal cycle from maximum to minimum daily temperature.



33°C. This phenomenon of reduced HI with supra-optimal temperature is observed in many different crops (Boote et al., 2005).

4.2 Simulating fresh fruit yield of tomato, fresh fruit size and maturation

Tomato is marketed as fresh weight, but CROPGRO, similar to most crop models, internally predicts dry matter accumulation and distribution. The CROPGRO-Tomato model has an algorithm that predicts dry matter concentration of individual fruit cohorts as a function of fruit thermal age. This function is described in Boote and Scholberg (2006). From the simulated dry matter concentration for successive fruit cohorts and simulated dry weight per fruit, the fresh weight size and diameter of individual fruits are computed (and can be output if desired). Then, the fresh weight of all fruits is integrated over all fruit cohorts to give total fruit fresh weight yield. While immature fruits may be as high as 12% dry matter, the dry matter concentration of harvestable tomato fruits varies from 5.1 to 6.4%, depending on season, cultivar, temperature and salinity (De Koning, 1993, 1994). The relationship of fruit diameter versus fresh mass for fruits of different shape (Bussieres, 1993) can be used to predict fruit diameter. Based on this approach, individual fruits can be assigned to specific size and/or grading classes to facilitate the prediction of marketable fruit yield. The end of fruit growth and maturation per cohort can be based on thermal time. A critical temperature sum needs to be reached over each individual fruit growth period for fruits to achieve maturity (Heuvelink, 2005). Perry et al. (1997) used this concept of growing degree days based on a threshold base temperature to predict tomato harvest in Southeastern United States. The temperature effect is strong, as Adams et al. (2001) and Adams and Valdes (2002) reported that when tomato plants were grown at 14, 18, 22 and 26°C, fruits ripened after 95, 65, 46 and 42 days, respectively. They found that the rate of fruit maturation was more sensitive to elevated temperature in later stages of fruit

Figure 4 Simulated fruit dry matter yield and total crop biomass, resulting from all temperature parameterizations in the CROPGRO-Tomato model, assuming a 10°C diurnal cycle from maximum to minimum daily temperature and a fixed solar irradiance of 21 MJ m–2.



growth. De Koning (1996, 2000) reported very similar temperature effects on the duration of the tomato fruit growth period. The CROPGRO-Tomato model predicts time to maturity for the total crop, but it does not yet have a method to output when given individual fruit cohorts are mature. Simulating output of only the mature fresh fruit yield is a needed step. Possibly, it is as simple as checking against fruit thermal age and ‘putting fruits into a mature box’ once they reach that age.


5.1 Water balance in the CROPGRO-Tomato modelWater balance follows the same principles as those of all DSSAT models. Soil water balance is a function of inputs from rainfall and irrigation, losses to soil evaporation (unless plastic mulch is used, which is simulated in a new not yet public version with drip irrigation; see Jones et al., 2014), crop transpiration, runoff and deep drainage. The soil water balance uses the tipping bucket approach of Ritchie (1998), in which water drains through successive layers when soil water content in the layer is greater than the drained upper limit (DUL). Soil evaporation is based on the Suleiman and Ritchie (2004) approach. Soil water uptake from each layer depends on the root length density in each layer and the soil water content of each layer. Potential root water uptake is the sum of potential root water uptake integrated over each of the soil layers. Normally, potential root water uptake exceeds the transpiration demand until the soil begins to dry. The potential transpiration (EPp) demand by the canopy is computed by using an energy-extinction coefficient, crop LAI and ET method. The methods include Priestley and Taylor (1972) or the FAO-56 described by Allen et al. (1998) as implemented in CROPGRO by Sau et al. (2004), but wind and dewpoint data are required for the FAO-56 method. When the potential root water uptake is less than the transpiration demand by the canopy, then the actual transpiration (EPa) and daily photosynthesis are reduced in proportion to the ratio of actual root water uptake/potential transpiration (EPa/EPp). Leaf area expansion and height increase are reduced before photosynthesis is reduced. See Boote et al. (2009) for further details on soil–crop–water balance in the CROPGRO model.

5.2 Nitrogen balance in the CROPGRO-Tomato modelThe CROPGRO model has N balance that simulates potential N uptake from soil as a function of root length density and soil nitrate and ammonium concentration in each soil layer. The daily crop N demand depends on today’s dry matter growth per organ type, and the target (critical desired) N concentration for each organ. Actual daily N uptake is the minimum of the two functions (potential N uptake and N demand), and thus can be limited by insufficient soil-available N. If this occurs, N uptake is less and the N concentration of the new growing organs is reduced. N deficiency creates a feedback on growth because when leaf N concentration is reduced over time, then leaf photosynthesis is reduced and subsequent total plant growth and leaf area expansion are reduced. Nitrogen mobilizes



continuously from vegetative tissues (N can move from old tissue to young tissue), but mobilization is accelerated during reproductive growth when mobilized N goes to fruits and seeds. Thus, the leaf N concentration of vegetative tissues will decline over time, especially during reproductive growth. Decline in N concentration causes reduction in canopy assimilation and accelerated leaf senescence and abscission as leaves approach their minimum N concentration (specified in the species file). The outcome is declining LAI and declining productivity late in the crop cycle, associated with slower fruit growth. See Boote et al. (2008) for further details on N balance in the CROPGRO model. The present model has not been widely tested for N deficiency and response to N because most tomato-production environments are well fertilized. We know from experiments and literature that tomato leaves are much smaller under N deficiency, but maintain their specific leaf N status because the leaves are not only smaller but also thicker (higher specific leaf weight). But this concept of thicker leaves under N deficiency is not yet modelled.

6 Illustrating growth dynamics of the CROPGRO-Tomato model and evaluations against field data

Tomato growth models require calibration with field or greenhouse data before being successfully used for prediction purposes. This is necessary to gain confidence in the ability to predict for local conditions, even though the principles of model development should apply across more diverse environmental conditions. The early phases of development of the CROPGRO-Tomato model included considerable field data collection by Scholberg et al. (2000a, b). The adaptation process included not only use of information from the literature but also calibration of certain parameters based on field experiments for parameters not known from the literature or those that are site specific (Scholberg et al., 1997; Boote et al., 2012). Subsequently, Rybak (2009) and then Boote et al. (2012) followed up with additional model re-parameterization based on later experiments and more recent literature review. The simulated time course of total crop, leaf, stem and fruit mass is shown in Fig. 5 for the 1992 field experiment conducted at Bradenton, Florida, by Scholberg et al. (1997). The crop was grown in sub-irrigated plastic-mulch-bed system with no water or N limitations (and was simulated with no water or N limitations). The final observed total aboveground biomass and fruit dry mass were 10 030 and 6620 kg ha–1, respectively, compared to simulated values of 10 460 and 6840 kg ha–1. The model simulated a final fresh fruit weight of 139 500 kg ha–1 for that season, with a simulated dry matter concentration of 5% at harvest. The model was well calibrated with ten seasons of experiments at three sites in Florida (see Boote et al., 2012, for more specifics). The model reproduces fruit yield differences caused by weather and site variation, as shown in the predicted fruit dry mass yield at Bradenton, Gainesville and Quincy, Florida (Fig. 6). The Bradenton site was transplanted on day 64 of the year, whereas the Quincy and Gainesville sites were transplanted on day 87 and days 95–97, respectively, and additionally there was an autumn crop transplanted on day 199 at Quincy. The Quincy and Gainesville sites are more continental and had warmer summer temperatures that caused the lower production shown in Fig. 6. The elevated temperatures in summer were the primary cause for lower fruit yield when planting was done later in spring. In addition, simulated production for



monthly sowing dates in November, December and January at the Gainesville location resulted in simulated crop failure from freeze damage, and the simulated October 1 sowing was terminated by frost.

Figure 7 illustrates the simulated and observed number of tomato fruits over time for the 1992 experiment at Bradenton. Fruit addition occurs over a nearly 30-day period and

Figure 5 Simulated and observed total crop, leaf, stem and fruit dry mass over time for the 1992 field experiment conducted at Bradenton, Florida. Data from Scholberg et al. (1997).

Figure 6 Simulated and observed tomato fruit dry mass over time for five Florida experiments established at different dates and sites (1992-Bradenton, 2006-Gainesville, 2007-Gainesville, 1995-spring-Quincy and 1995-autumn-Quincy).



then stabilizes at a point where the crop-carrying capacity has been reached by about 80 days after planting. Notice in Fig. 5 that leaf and stem (all vegetative growth) of this semi-determinate tomato ceased and achieved a plateau at 80 days.

7 Simulating tomato growth and yield response under N-limited and water-limited conditions

7.1 Simulating tomato growth and yield response to N under N-limited conditions

A hypothetical study of tomato yield response to N deficiency is illustrated in Fig. 8 and 9, for rates of 0, 20, 40, 80, 120, 160, 200 and 240 kg N ha–1 applied in splits on day 1 and day 41 for a crop growing in Florida with a hypothetical mulch-plastic bed (irrigation was supplied by an auto-irrigate feature in the model and rainfall was set to zero to prevent N leaching). The course of fruit growth over time (Fig. 8) shows dramatic response to N fertilization up to the highest rate of 240 kg N ha–1. The total crop N uptake was 239 kg N ha–1 and only 29 kg N ha–1 was simulated to be mineralized from this sandy soil during the experiment. The fertilizer N requirement would have been less on a more fertile, higher organic carbon soil. Figure 9 illustrates that lower N fertilization resulted in lower leaf N concentration associated with N deficiency, which reduced assimilation and reduced biomass growth (not shown) as well as fruit dry matter growth. At least 120 kg N ha–1 was required to sustain leaf N concentration at optimum target during vegetative growth; however, even at that rate, the leaf N concentration declined early during fruit growth (Fig. 9), resulting in a reduced yield (Fig. 8), although leaf N concentration and yield could be sustained by higher N application.

Figure 7 Simulated and observed number of tomato fruits per m2 over time for the 1992 Bradenton experiment (data from Scholberg et al., 1997).



7.2 Simulating tomato growth and yield response to irrigation under water-limited conditions

Industrial tomato production is sometimes done under water-limited conditions. The CROPGRO-Tomato model can be used to simulate irrigation strategies for tomato production (as done by Rinaldi, 2007; Rinaldi et al., 2007), and can also be used to simulate transpiration and irrigation requirements. Figure 10 illustrates total crop dry weight

Figure 8 Simulated fruit dry mass over time as affected by N fertilization (0 to 240 kg N ha–1) for the 1992 field experiment conducted at Bradenton, Florida. Observed tomato dry weight data are for highly N-fertilized treatment of Scholberg et al. (1997).

Figure 9 Simulated leaf N concentration over time as affected by N fertilization (20 to 240 kg N ha –1) for the 1992 field tomato experiment conducted on a sandy soil at Bradenton, Florida.



over time as affected by differential irrigation thresholds (cm depth of control and per cent available soil water at which irrigation is applied) for the 1992 tomato field experiment at Bradenton, Florida. (To achieve the simulated water deficit, rainfall was reduced to 30% of the actual for all treatments, and the initial soil water was reduced for the two most severe treatments.) The hypothetical water limitation reduced dry matter accumulation in total crop (Fig. 10) as well as in fruit dry matter yield (Fig. 11). Water deficit severely reduced photosynthesis, transpiration, LAI, crop dry matter and fruit yield. Transpiration amounts were 266, 217, 172, 127 and 57 mm for the five irrigation treatments, respectively. The model simulated earlier maturation under water deficit. These two figures are hypothetical examples of water deficits that can be simulated with the model, but further tests with real experiments are needed.

8 Summary

The CROPGRO-Tomato model can be used by producers to manage their tomato crop in several ways: (1) predicting probable maturity date and yield, for a given particular year weather pattern or prior long-term weather, (2) optimizing irrigation strategies based on simulated transpiration water demand, (3) optimizing fertilizer N strategies, based on simulated growth response to N fertilizer applications and (4) predicting fruit size and size distribution relative to past weather experienced. Sustainability of production relative to water and fertilizer N resources can be important for producers. The CROPGRO-Tomato model was used successfully by Rinaldi (2007) to evaluate irrigation strategies for field-grown processing tomato relative to long-term weather. Rinaldi concluded that the model was a useful decision-support system to help farmers evaluate optimal irrigation

Figure 10 Simulated total crop dry weight over time as affected by differential irrigation thresholds (depth of control in cm, and per cent available soil water at which irrigation is applied) for the 1992 tomato field experiment conducted at Bradenton, Florida. Observed dry weight data are for the well-irrigated treatment of Scholberg et al. (1997).



management strategy. In another application, Rinaldi et al. (2007) used the model to evaluate optimal N-fertilization strategies for field-grown tomato under differential water management, with the goal of minimizing N leaching into the groundwater while sustaining good tomato production. These dual goals are important in many tomato-producing areas where the soils are sandy and are susceptible to N leaching into ground water. See Boote et al. (1996) for a review of the various uses and limitations of crop models.


A new not yet public version of the model has been developed by Jones et al. (2014) in which a two-dimensional soil bed is simulated with plastic mulch and drip irrigation. This version will enhance simulations of mulch-plastic-bed field tomato crops for the following reasons: (1) drip irrigation is mechanistically simulated with Green-Ampt flow of water and soluble fertilizer N in the water from the drip tape, (2) rainfall is shed by the plastic mulch, thus minimizing rainfall-induced N leaching from the bed and yielding a more realistic crop response to N applied for mulched tomato, (3) soil evaporation is minimized by the plastic mulch portion of the bed, more correctly reproducing soil evaporation and transpiration and (4) root growth patterns in the bed are more realistically simulated (roots tend to follow the provided water and fertility).

Another development in process is the parameterization and adaptation of the model to simulate P deficiency (based on soil P test) and P-fertilizer application. This research is in process with Brazilian colleagues, and will be available in a future DSSAT release in one or two years. The P-response version of the model will be useful in tropical and other regions of the world where phosphorus deficiency is serious, and soil testing is available.

Figure 11 Simulated fruit dry weight over time as affected by differential irrigation thresholds (depth of control in cm, and per cent available soil water at which irrigation is applied) for the 1992 tomato field experiment conducted at Bradenton, Florida. Observed dry weight data are for the well-irrigated treatment of Scholberg et al. (1997).



With some code modification, it may be possible to have the model simulate as a single-stem greenhouse tomato, or to do model predictions of sequential harvests of indeterminate cultivars, in contrast to the present single harvest of semi-determinate field cultivars.


• Description of the CROPGRO-Tomato model: Boote, K. J., M. R. Rybak, J. M. S. Scholberg and J. W. Jones. 2012. Improving the CROPGRO-Tomato model for predicting growth and yield response to temperature. HortScience 47: 1038–49.

• Overview paper on the DSSAT crop modeling software: Jones, J. W., G. Hoogenboom, C. H. Porter, K. J. Boote, W. D. Batchelor, L. A. Hunt, P. W. Wilkens, U. Singh, A. J. Gijsman and J. T. Ritchie. 2003. The DSSAT cropping system model. European Journal of Agronomy 18: 235–65.

• Go to: www.dssat.org, for further information on DSSAT crop models, to download the DSSAT software along with CSM-CROPGRO-Tomato.

• Go to: www.agmip.org, for information on the Agricultural Model Intercomparison and Improvement Project (AgMIP), a consortium of international scientists using climate, crop and economic models to evaluate the effects of climate change and climate variability on crop production and food security including economic consequences.

• Hortimodel conference held every two to three years, a conference that specializes in reporting on modelling of horticultural and greenhouse crops.

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Suleiman, A. A., and J. T. Ritchie. 2004. Modification to the DSSAT vertical drainage model for more accurate soil water dynamics estimation. Soil Science 169: 745–57.

Xu, H.-L., L. Gauthier, Y. Desjardins and A. Gosselin. 1997. Photosynthesis in leaves, fruits, stem and petioles of greenhouse-grown tomato plants. Photosynthetica 33: 113–23.

http://dx.doi.org/10.1007/978-94-017-3624-4_3

http://dx.doi.org/10.9734/ajea/2015/14806

http://dx.doi.org/10.1046/j.1365-3040.2000.00589.x

http://dx.doi.org/10.1093/jexbot/53.371.1187


http://dx.doi.org/10.1007/978-94-017-0754-1_9



http://dx.doi.org/10.1097/01.ss.0000148740.90616.fd

http://link.springer.com/article/10.1023%2FA%3A1022135507700

References

1 Chapter 1 Modelling crop growth andyield in tomato cultivation

1 Introduction

Crop-growth simulation models have become important toolsfor researchers and growers

for the purpose of assisting management and improvingproduction. The CROPGRO

Tomato model described in this chapter is one of a suite ofmodels within the modelling

package Decision Support System for Agrotechnology Transfer(DSSAT), which is widely

used and accepted by agricultural research communities(Jones et al., 2003). This model

is mechanistic and process oriented (processes of carbon,water and N balance), and it

simulates daily progress towards flowering and fruit set aswell as daily growth of leaves,

stems, roots and fruits over time until maturity or finalharvest (Scholberg et al., 1997;

Boote et al., 1998; Boote et al., 2012). This chapterdescribes the model, its sensitivity

to climatic and management factors, what it is capable ofpredicting and how it can be

used in various applications of tomato (Solanumlycopersicum Mill.) cultivation in order to

address the challenges confronting industry and researchers.

2 Review of tomato crop modelling and introduction ofthe CROPGRO-Tomato model

2.1 Brief review of tomato crop modelling and somechallenges

A number of prior efforts directed towards tomato growthmodelling are reviewed here.

Many of those models (Jones et al., 1991; Dayan et al.,1993; Heuvelink, 1995, 1996; Marcelis

et al., 1998) are designed for single-stem indeterminategrowth of tomato in greenhouse

conditions, and generally simulate growth and yield underfull nitrogen nutrition. (The

models do not address N stress or P stress.) TOMGRO is arelatively simple single-stem

indeterminate tomato model developed by Jones et al. (1991)that predicts growth of

successive leaves and successive fruit trusses and fruitproduction under non-limiting N

conditions in greenhouse. The tomato models developed byHeuvelink (1995, 1996) and

Marcelis et al. (1998) are more detailed and mechanisticcompared to the TOMGRO model;

they are designed for predicting the growth and yield ofindeterminate greenhouse

produced tomato. Their models are quite mechanistic andsimulate photosynthesis,

respiration and fruit setting and growth using explicitsink strength of fruits and vegetative

organs. In some cases, tomato models are included withinsimulations of greenhouse

environment as an entire system, and the combined system isused as a horticultural

management and teaching tool (Gary et al., 1997, 1998). TheTOMGRO model (Jones

et al., 1991; Dayan et al., 1993) and the Tompousse modeldeveloped by Abreu et al.

(2000) are designed to predict greenhouse-grown tomato. TheCROPGRO-Tomato

model described in this chapter is designed to predict

daily growth and yield of field

grown, semi-determinate tomato under limited water andnutrient conditions in the field.

Development of the CROPGRO-Tomato model began in 1996(Scholberg, 1996; Scholberg

et al., 1997), and the model was recently more fully testedand improved for temperature

parameterization by Boote et al. (2012). It has been usedto evaluate N fertilization and

irrigation strategies for tomato in southern Italy(Rinaldi, 2007; Rinaldi et al., 2007).

Challenges for modelling tomato production include (1)accurately simulating life

cycle and maturation of fruits and yield responses totemperature, whether field or

greenhouse; (2) simulating response to soil wateravailability for a range of production

systems, including open-field and mulch-bed systems; (3)simulating response to fertility

(N or P); (4) simulating fresh weight of fruits and fruitsize distributions and (5) modelling

the genetic variation relative to fruit set, fruit size,maturation and yield. From the prior

brief review of models for tomato, it is clear thatpredicting production in greenhouse

environments is important, including control of greenhousetemperature and CO 2

environment. In both field and greenhouse production,growers want to know the

progress of their crop under the past and projected weatherconditions for predicting fruit

maturation and harvest for marketing. Fruit sizedistribution is important for marketing.

Future collaboration of crop modellers with tomato breederscan be beneficial, not just to

better characterize production in producer fields, but toassist breeders in hypothesizing

the benefits of heat-tolerant traits, for example, instressful environments.

2.2 Description of the CROPGRO-Tomato model

The CROPGRO model was initially developed for annual graincrops, especially grain

legumes (Boote et al., 1998); but being a generic model, itwas easily adapted for other

annual crops, including non-legumes, by turning off theN-fixation aspect and predicting

fruit mass rather than seed mass as done in the adaptationby Scholberg et al. (1997)

for semi-determinate field-grown tomato. CROPGRO is ageneric model that uses one

common FORTRAN code for all of its crops, but requires adetailed species file for many

parameterizations that include initialization, tissuecomposition and relationships defining

the sensitivity of the crop processes to light, water,temperature and N status (see Boote

et al., 1998). The model is generic in the sense that thereare no hard-wired parameters

or equations inside the code. This allowed Scholberg (1996)to start with a template

species file from one of the grain legumes and modify it topredict tomato, including its

compositions and sensitivity to environmental factors. Thisprocess required careful review

of the tomato literature to glean appropriate parameters,along with field experiments, to

check the predictions of the model and to calibrate speciesmodel parameters for which

there is no published literature. There is also a cultivarfile and an ecotype file with a lesser

number of genotype-specific parameters that describe thetomato life cycle and other

traits (e.g. time to first flower, time to maturity, rateof leaf appearance, leaf size, fruit size,

rate of fruit addition etc.) for the cultivar beingpredicted. The adaptation by Scholberg

et al. (1997) provided a model that was initiallyfunctional, but that version benefitted

from several later improvements to allow prediction offruit fresh weight, fruit size and

fruit dry matter concentration (Boote and Scholberg, 2006),with additional improvements

resulting from the work of Rybak (2009), who measuredtime-series growth characteristics

of individual tomato fruits from three successive cohortsunder differential water and

N-fertility conditions. Subsequently, Boote et al. (2012)did a thorough review of the recent

tomato literature and completely re-parameterized thesensitivity of photosynthesis,

vegetative growth, fruit set and fruit growth aspects totemperature. Current work in

progress with Brazilian colleagues is adding sensitivity toP fertility and P fertilization

as well as re-parameterizing the model for N-limitedconditions. Therefore, after these

improvements, the CROPGRO-Tomato model promises to be arobust one adapted for

predicting the growth and yield of semi-determinatecultivars under field conditions where

water and N- and P-limited conditions prevail.

3 Important processes and temperature sensitivities inthe CROPGRO-Tomato model

The CROPGRO-Tomato model is process oriented andmechanistic and simulates the

various processes of crop development, crop carbon balance,crop N balance, soil–crop

water balance and soil N balance. The model uses a one-daytime step, except for hourly

time steps for the leaf-to-canopy assimilation module. Itrequires daily weather inputs

(solar radiation, maximum temperature, minimum temperatureand rainfall), soil water

holding characteristics, soil N-supplying characteristics,crop cultivar characteristics and

management information (transplanting date, row spacing,plant spacing, irrigation and

fertilization).

3.1 Crop development

The model considers both vegetative and reproductivedevelopment as a function of

temperature and plant water status, simulating the rate ofsuccessive leaf formation

on the main stem and the rate of progress towardsreproductive stages (first flower,

beginning fruit etc.). Simulated successive node number onthe main axis is used to

influence leaf area expansion of successive leaves duringthe first five or so leaves

produced and also influences the partitioning of assimilateto leaf, stem and root

tissue (using a partitioning look-up as a function of

current vegetative node number).

The reproductive progression (to anthesis, to first fruit,duration of fruit formation and

duration from first fruit to beginning fruit maturity)defines the crop life cycle, as well as

affecting the partitioning of assimilate to fruits, rate offruit addition and duration of fruit

growth to maturity. Reproductive progression is primarilyaffected by temperature, and

the model uses cardinal temperatures of base temperatureand optimum temperature to

compute photothermal days per calendar day, which aresummed up and compared to

the photothermal day requirements to trigger the nextreproductive stage. To account

for the dependence of processes on temperature, theCROPGRO-Tomato model uses

four-point temperature response functions represented by(1) base temperature (T b ), the

temperature below which the rate of the process is zero;(2) T opt1 , the lowest temperature

at which maximum rate is attained; (3) T opt2 , the uppertemperature at which maximum

rate is sustained and (4) maximum temperature, T fail , thetemperature above which the

rate is zero. Temperature functions for nearly allprocesses in CROPGRO are computed

hourly following 24-hour diurnal temperatures simulatedfrom daily T max and T min ; thus

the functions for processes are the average over the hourlytemperatures. Based on

temperature experiments of Adams et al. (2001) and asreviewed in Boote et al. (2012), the

CROPGRO-Tomato model uses 7, 22, 28 and 48°C for T b , Topt1 , T opt2 and T fail , respectively,

in the species parameter input file as cardinaltemperatures for vegetative development

and rate of progress towards anthesis. For progress fromanthesis to maturity and for fruit

development and maturation, the temperature functions usecardinal temperature values

of 5.2, 26, 28 and 48°C for T b , T opt1 , T opt2 and Tfail , respectively. Figure 1 shows the effect of

those functions on days to anthesis and days to maturity,where the temperature shown

Figure 1 The simulated effect of temperature functions forreproductive development upon days to

anthesis and days to maturity, versus mean dailytemperature simulated assuming a 10°C diurnal cycle

from maximum to minimum daily temperature.

is the result of a 10°C differential from maximum tominimum daily temperature. The

experimental knowledge and confidence of the response above28°C is low.

3.2 Carbon balance and photosynthesis

The model’s carbon balance considers C inputs fromphotosynthesis, C losses to respiration

and losses to senescence and abscission, as well as thepartitioning of assimilate to the

different organs (leaves, stems, roots and fruits). TheCROPGRO-Tomato model simulates

single-leaf photosynthesis scaled up to hedgerow canopyassimilation (Boote and

Pickering, 1994), where leaf photosynthesis sensitivity toCO 2 , light, temperature and leaf

N concentration is parameterized from literature

information. The leaf photosynthesis

module combines an asymptotic exponential equation with amodified Farquhar and von

Cammerer (1982) approach. Both the light-saturated leafassimilation rate (A max ) and the

quantum efficiency are then moderated by temperature, CO 2and O 2 functions (Boote and

Pickering, 1994; Pickering et al., 1995). Leafphotosynthesis is predicted hourly for sunlit-

and shaded-leaf classes in the canopy and is multipliedhourly by sunlit leaf area index

(LAI) and shaded LAI, and scaled or integrated up to dailygross photosynthesis, following

Boote and Pickering (1994). This method of scaling up fromleaf-to-canopy assimilation

has been shown to predict accurate responses to light, CO 2and LAI for grain legumes

(Boote and Pickering, 1994; Alagarswamy et al., 2006) andmaize (Lizaso et al., 2005a,

b). The cultivar parameter, A max , light-saturated leafphotosynthesis, is a conservative

parameter based on literature reports for tomato (Xu etal., 1997; Barrios-Masias et. al.,

2014), and this trait does not vary much across cultivars.The work by Boote et al. (2012)

describes parameterization of the temperature-dependentprocesses of light-saturated

leaf photosynthesis for the model. The T b , T opt1 , Topt2 and T fail , respectively, for hourly

temperature effect on light-saturated, CO 2 -saturated leafphotosynthesis is 6, 26, 34

and 48°C, respectively. These instantaneous temperatureoptimums agree with values

reported by Heuvelink and Dorais (2005). There is also aminimum night temperature

effect on the model that reduces the next day’s leafphotosynthesis, which concurs with

reported reductions in photosynthesis of tomato when the Tmin (night temperature) is

below 10°C (Martin et al., 1981; Byrd et al., 1995). Anasymptotic function reduces leaf

photosynthesis beginning at T min of 15°C, going to zerorate at T min of �2°C. The T b and

T opt values were, in part, based on literature as well ascalibration and optimization against

dry matter accumulation in cool versus warm seasons inFlorida (Boote et al., 2012). The

model accounts for both growth respiration and maintenancerespiration. The growth

respiration approach follows that of Penning de Vries etal. (1974), in which the cost of

synthesizing tissue depends on the approximate composition(carbohydrate, protein,

lipid, lignin, organic acid and mineral) of each organ andthe biochemical pathways to

synthesize those broad classes of compounds. The tomatomodel species file contains

the compositions for plant organs (leaf, stem, root, fruitand seed), as well as the costs

given by Penning de Vries and van Laar (1982). In addition,the model considers daily

maintenance respiration as a combined function based ontotal crop mass and daily gross

photosynthesis. Maintenance respiration is sensitive totemperature, but growth respiration

efficiency is not temperature sensitive. Modelled leaf areaexpansion (via specific leaf area

of new leaves) also has temperature dependency, beingreduced at very low or very high

temperature. An important point not mentioned is that theCROPGRO model handles

transplants of tomato as a way of initializing the model,where the size of the transplant, as

well as an estimate of prior seedling growth temperatureconditions, is needed.

3.3 Carbon balance and setting of fruits

The model is source driven, in which the amount of dailyassimilate determines the growth

of leaves (including leaf area), stems, roots and fruits.Before rapid fruit growth, the

partitioning among organs varies with the vegetative stage(node number on main stem,

which is a type of thermal accumulator). Once fruitaddition begins, explicit numbers of

successive daily fruit cohorts are added (along withexplicit sink strengths per fruit). The

set fruits have first priority for assimilate overvegetative tissues, and the crop continues

to flower and add fruits each day as long as assimilatesare available. During this phase,

vegetative and root growth will be progressively reduced asmore fruits are added, but

only up to a carrying capacity called XFRUIT. XFRUIT is acultivar trait that specifies the

maximum fraction of assimilate that can be allocated tofruits at the final point of fruit

addition. This value can be 0.70 to 0.80 for typicalsemi-determinate cultivars, which

means that the remaining fraction (1.00 – XFRUIT) isreserved for vegetative growth. This

would correspond to the concept of constant vegetative sinkstrength relative to each

successive truss added on plants simulated in the TOMSIMmodel (Heuvelink, 1996). For

true indeterminate cultivars, the practical XFRUIT may beas low as 0.50, created in part by

genetics, but also by the practice of pruning to one or twomain stems and also pruning

and harvesting fruits, so as to sustain growth of theapical vegetative-growing meristems.

The model can be simulated as an indeterminate plant byusing a low XFRUIT, if desired,

with a very long crop cycle, continued fruit set anddelayed senescence.

3.4 Fruit cohorts and temperature effects on fruit setand growth per fruit

The CROPGRO model has flower and fruit cohorts, withexplicit addition of flowers added

each day after the beginning flower date. For each dailycohort, the individual flowers

progress to form fruit cohorts after a thermally dependentshort phase (called FL-SH in

the model). Growth rate per fruit then has a slow phasestarting immediately after flower

opening, followed by a rapid phase (see Boote et al., 2012for more complete description

of this). The decision to carry or abort each successivefruit depends on a temperature

stress function and assimilate availability – the modelchecks to see if the carrying capacity

has been reached relative to demand from all prior fruits,similar to Bertin (1995, 2005)

and the sink to source ratio of Marcelis et al. (2004). The

CROPGRO-Tomato species

file contains a temperature function for fruit additionthat mimics elevated temperature

effects on flower fertility. Fruit set for eachflower–fruit cohort depends on the temperature

during the flower to fruit-set phase, and the fraction offruits set (or aborted) follows an

hourly temperature-dependent function described by therange T opt1 to T opt2 (optimum

temperature) and T fail (too hot, zero pollination). Thetemperature range for fruit setting

in tomato is narrow and especially the night temperature iscritical. The optimal range

reported for fruit setting in tomato is reported to be 18to 20°C (De Koning, 1994). Fruit

set is low at both low and excessively high temperatures.Hot conditions may result in

cone splitting, stigma exertion and pollen sterility, andmaximal day temperature in excess

of 32°C and/or minimal night temperature above 21°C greatlyreduce fruit set (Moore and

Thomas, 1952; Benedictos and Yavari, 2000). Therefore, thecardinal temperatures of 6,

21, 26 and 33°C were used by Boote et al. (2012) as T b , Topt1 , T opt2 and T fail , respectively,

for fruit setting (fruit addition rate) and pollination(Fig. 2), based considerably on these

data and those of Adams et al. (2001), except that Adams etal. did not explore values

for ceiling failure temperature. It is likely thatdifferences exist in the upper thresholds for

heat-tolerant versus heat-sensitive tomato cultivars (Loharand Peat, 1998; Sato et al.,

2000). Sato et al. (2002) reported that pollen viability isadversely affected by elevated

temperature (32/26°C) occurring during the approximateten-day period prior to flower

opening, during which time the pollen is formed anddeveloped.

The growth rate of individual fruits is dependent on bothassimilate supply and

temperature following a temperature-dependentparameterization. Fruit growth rate

follows a genetic potential rate as modified bytemperature, although after a full fruit

load is set (plant has reached carrying capacity), theremaining fruits share a deficit if

assimilate deficit occurs. This feature works sufficientlywell in the model to mimic the

significant distribution of fruit sizes, as the early-setfruits have much less competition

and are larger than late-set fruits (Bohner and Bangerth,1988; Rybak, 2009; Rybak et al.,

2015). Experiments of Fanwoua et al. (2012) reported animportant role of sugar content

and timing of assimilate supply on variation in fruit size.For parameterizing temperature

effects on fruit growth rate, optimum temperatures of 26°Cwere reported by Rylsky

(1979), whereas Adams et al. (2001) found an optimumregimen of 25/25°C (day/night).

Values for base temperature and ceiling temperature for thefruit growth rate are difficult

to obtain. In the absence of data on ceiling temperatureeffects on fruit growth, a T fail

(32°C) for fruit growth rate was assumed close to that offruit addition and pollination

(33°C). In addition, a T b of 6°C was used to be close tothe T b values used for vegetative,

reproductive and fruit-set processes. Thus, cardinaltemperatures used in the model for

fruit (and seed) growth rate are 6, 22, 25 and 32°C for T b, T opt1 , T opt2 and T fail , respectively,

as shown in Fig. 2 (Boote et al., 2012). In addition, theCROPGRO-Tomato species

file includes a function that modifies the partitioninglimit to fruit growth (XFRUIT) if

temperature is high (reduced above 28°C and falling to zeroat 34°C), and this function is

an additional contributor to elevated temperature effectson fertility in the model (Boote

and Scholberg, 2006).

Figure 2 Shape of parameterization of relative temperatureeffect on fruit set (addition), individual

fruit growth rate and on maximum fraction partitioningallowed to fruits for the CROPGRO-Tomato

model.

4 Integrating temperature effects and simulating growthand yield for tomato crops

4.1 Integrated effects of temperature functions on yield,crop mass, fruit numbers and fruit size

The result of these parameterizations of temperatureeffects on fruit set, fruit growth

rate and partitioning to fruits is that simulated tomatofruit set is limited by elevated

temperature, fruit numbers are reduced and fruit size isreduced as temperature

increases (Fig. 3); total fruit growth and final fruityield are reduced (Fig. 4). Simulated

fruit number is relatively stable as high as 24°C, but isprogressively reduced at higher

mean temperatures, falling to zero at 33°C, as regulated bythe functions shown in

Fig. 2. Simulated fruit size declines rather continuouslyas temperature increases (Fig. 3),

caused not only by the temperature effect on the rate ofsingle fruit growth, but also

by the temperature effect on the duration of fruit growth,which is longer when the

temperature is cooler. The simulated temperature effect onfruit size concurs with the

general knowledge of observed temperature effects, butadditional testing is needed

to evaluate the robustness of the model predictions. Aconsequence of all these

temperature-effect parameterizations as well as onphotosynthesis is that simulated crop

total biomass and fruit yield are reduced as temperatureincreases (Fig. 4). The higher

final crop biomass simulated at cool temperature is causedby longer cycle duration and

not by higher photosynthesis. The higher fruit yield atcool temperature is caused by

longer fruit growth duration as well, until above 24°C, atwhich temperature the model

functions begin to affect fruit set, fruit growth rate andpartitioning, thus reducing the

yield to zero at 33°C. Simulated fruit dry weight harvestindex (HI) is about 0.70 at cooler

temperatures, but HI begins to be reduced progressivelyabove 24°C, falling to zero at

Figure 3 Simulated fruit number per m 2 and fresh weightper fruit, resulting from all temperature

parameterizations in the CROPGRO-Tomato model, assuming a10°C diurnal cycle from maximum to

minimum daily temperature.

33°C. This phenomenon of reduced HI with supra-optimaltemperature is observed in

many different crops (Boote et al., 2005).

4.2 Simulating fresh fruit yield of tomato, fresh fruitsize and maturation

Tomato is marketed as fresh weight, but CROPGRO, similar tomost crop models, internally

predicts dry matter accumulation and distribution. TheCROPGRO-Tomato model has an

algorithm that predicts dry matter concentration ofindividual fruit cohorts as a function

of fruit thermal age. This function is described in Booteand Scholberg (2006). From the

simulated dry matter concentration for successive fruitcohorts and simulated dry weight

per fruit, the fresh weight size and diameter of individualfruits are computed (and can

be output if desired). Then, the fresh weight of all fruitsis integrated over all fruit cohorts

to give total fruit fresh weight yield. While immaturefruits may be as high as 12% dry

matter, the dry matter concentration of harvestable tomatofruits varies from 5.1 to 6.4%,

depending on season, cultivar, temperature and salinity (DeKoning, 1993, 1994). The

relationship of fruit diameter versus fresh mass for fruitsof different shape (Bussieres, 1993)

can be used to predict fruit diameter. Based on thisapproach, individual fruits can be

assigned to specific size and/or grading classes tofacilitate the prediction of marketable

fruit yield. The end of fruit growth and maturation percohort can be based on thermal

time. A critical temperature sum needs to be reached overeach individual fruit growth

period for fruits to achieve maturity (Heuvelink, 2005).Perry et al. (1997) used this concept

of growing degree days based on a threshold basetemperature to predict tomato harvest

in Southeastern United States. The temperature effect isstrong, as Adams et al. (2001)

and Adams and Valdes (2002) reported that when tomatoplants were grown at 14, 18,

22 and 26°C, fruits ripened after 95, 65, 46 and 42 days,respectively. They found that the

rate of fruit maturation was more sensitive to elevatedtemperature in later stages of fruit

Figure 4 Simulated fruit dry matter yield and total cropbiomass, resulting from all temperature

parameterizations in the CROPGRO-Tomato model, assuming a10°C diurnal cycle from maximum to

minimum daily temperature and a fixed solar irradiance of21 MJ m –2 .

growth. De Koning (1996, 2000) reported very similartemperature effects on the duration

of the tomato fruit growth period. The CROPGRO-Tomato modelpredicts time to maturity

for the total crop, but it does not yet have a method tooutput when given individual fruit

cohorts are mature. Simulating output of only the maturefresh fruit yield is a needed

step. Possibly, it is as simple as checking against fruitthermal age and ‘putting fruits into

a mature box’ once they reach that age.


5.1 Water balance in the CROPGRO-Tomato model

Water balance follows the same principles as those of allDSSAT models. Soil water

balance is a function of inputs from rainfall andirrigation, losses to soil evaporation

(unless plastic mulch is used, which is simulated in a newnot yet public version with drip

irrigation; see Jones et al., 2014), crop transpiration,runoff and deep drainage. The

soil water balance uses the tipping bucket approach ofRitchie (1998), in which water

drains through successive layers when soil water content inthe layer is greater than

the drained upper limit (DUL). Soil evaporation is based onthe Suleiman and Ritchie

(2004) approach. Soil water uptake from each layer dependson the root length density

in each layer and the soil water content of each layer.Potential root water uptake is the

sum of potential root water uptake integrated over each ofthe soil layers. Normally,

potential root water uptake exceeds the transpirationdemand until the soil begins to

dry. The potential transpiration (EPp) demand by the canopyis computed by using an

energy-extinction coefficient, crop LAI and ET method. Themethods include Priestley

and Taylor (1972) or the FAO-56 described by Allen et al.(1998) as implemented in

CROPGRO by Sau et al. (2004), but wind and dewpoint data

are required for the FAO

56 method. When the potential root water uptake is lessthan the transpiration demand

by the canopy, then the actual transpiration (EPa) anddaily photosynthesis are reduced

in proportion to the ratio of actual root wateruptake/potential transpiration (EPa/

EPp). Leaf area expansion and height increase are reducedbefore photosynthesis is

reduced. See Boote et al. (2009) for further details onsoil–crop–water balance in the

CROPGRO model.

5.2 Nitrogen balance in the CROPGRO-Tomato model

The CROPGRO model has N balance that simulates potential Nuptake from soil as a

function of root length density and soil nitrate andammonium concentration in each soil

layer. The daily crop N demand depends on today’s drymatter growth per organ type, and

the target (critical desired) N concentration for eachorgan. Actual daily N uptake is the

minimum of the two functions (potential N uptake and Ndemand), and thus can be limited

by insufficient soil-available N. If this occurs, N uptakeis less and the N concentration of

the new growing organs is reduced. N deficiency creates afeedback on growth because

when leaf N concentration is reduced over time, then leafphotosynthesis is reduced and

subsequent total plant growth and leaf area expansion arereduced. Nitrogen mobilizes

continuously from vegetative tissues (N can move from oldtissue to young tissue), but

mobilization is accelerated during reproductive growth whenmobilized N goes to fruits

and seeds. Thus, the leaf N concentration of vegetativetissues will decline over time,

especially during reproductive growth. Decline in Nconcentration causes reduction in

canopy assimilation and accelerated leaf senescence andabscission as leaves approach

their minimum N concentration (specified in the speciesfile). The outcome is declining

LAI and declining productivity late in the crop cycle,associated with slower fruit growth.

See Boote et al. (2008) for further details on N balance inthe CROPGRO model. The

present model has not been widely tested for N deficiencyand response to N because

most tomato-production environments are well fertilized. Weknow from experiments

and literature that tomato leaves are much smaller under Ndeficiency, but maintain their

specific leaf N status because the leaves are not onlysmaller but also thicker (higher

specific leaf weight). But this concept of thicker leavesunder N deficiency is not yet

modelled.

6 Illustrating growth dynamics of the CROPGROTomato modeland evaluations against field data

Tomato growth models require calibration with field orgreenhouse data before being

successfully used for prediction purposes. This isnecessary to gain confidence in the ability

to predict for local conditions, even though the principlesof model development should

apply across more diverse environmental conditions. Theearly phases of development of

the CROPGRO-Tomato model included considerable field datacollection by Scholberg

et al. (2000a, b). The adaptation process included not onlyuse of information from

the literature but also calibration of certain parametersbased on field experiments

for parameters not known from the literature or those thatare site specific (Scholberg

et al., 1997; Boote et al., 2012). Subsequently, Rybak(2009) and then Boote et al. (2012)

followed up with additional model re-parameterization basedon later experiments and

more recent literature review. The simulated time course oftotal crop, leaf, stem and fruit

mass is shown in Fig. 5 for the 1992 field experimentconducted at Bradenton, Florida,

by Scholberg et al. (1997). The crop was grown insub-irrigated plastic-mulch-bed system

with no water or N limitations (and was simulated with nowater or N limitations). The

final observed total aboveground biomass and fruit dry masswere 10 030 and 6620 kg

ha –1 , respectively, compared to simulated values of 10460 and 6840 kg ha –1 . The model

simulated a final fresh fruit weight of 139 500 kg ha –1for that season, with a simulated dry

matter concentration of 5% at harvest. The model was wellcalibrated with ten seasons of

experiments at three sites in Florida (see Boote et al.,2012, for more specifics). The model

reproduces fruit yield differences caused by weather and

site variation, as shown in the

predicted fruit dry mass yield at Bradenton, Gainesvilleand Quincy, Florida (Fig. 6). The

Bradenton site was transplanted on day 64 of the year,whereas the Quincy and Gainesville

sites were transplanted on day 87 and days 95–97,respectively, and additionally there was

an autumn crop transplanted on day 199 at Quincy. TheQuincy and Gainesville sites are

more continental and had warmer summer temperatures thatcaused the lower production

shown in Fig. 6. The elevated temperatures in summer werethe primary cause for lower

fruit yield when planting was done later in spring. Inaddition, simulated production for

monthly sowing dates in November, December and January atthe Gainesville location

resulted in simulated crop failure from freeze damage, andthe simulated October 1

sowing was terminated by frost.

Figure 7 illustrates the simulated and observed number oftomato fruits over time for

the 1992 experiment at Bradenton. Fruit addition occursover a nearly 30-day period and

Figure 5 Simulated and observed total crop, leaf, stem andfruit dry mass over time for the 1992 field

experiment conducted at Bradenton, Florida. Data fromScholberg et al. (1997).

Figure 6 Simulated and observed tomato fruit dry mass overtime for five Florida experiments

established at different dates and sites (1992-Bradenton,2006-Gainesville, 2007-Gainesville,

1995-spring-Quincy and 1995-autumn-Quincy).

then stabilizes at a point where the crop-carrying capacityhas been reached by about 80

days after planting. Notice in Fig. 5 that leaf and stem(all vegetative growth) of this semi

determinate tomato ceased and achieved a plateau at 80 days.

7 Simulating tomato growth and yield response underN-limited and water-limited conditions

7.1 Simulating tomato growth and yield response to Nunder N-limited conditions

A hypothetical study of tomato yield response to Ndeficiency is illustrated in Fig. 8 and 9, for

rates of 0, 20, 40, 80, 120, 160, 200 and 240 kg N ha –1applied in splits on day 1 and day 41

for a crop growing in Florida with a hypotheticalmulch-plastic bed (irrigation was supplied

by an auto-irrigate feature in the model and rainfall wasset to zero to prevent N leaching).

The course of fruit growth over time (Fig. 8) showsdramatic response to N fertilization up

to the highest rate of 240 kg N ha –1 . The total crop Nuptake was 239 kg N ha –1 and only

29 kg N ha –1 was simulated to be mineralized from thissandy soil during the experiment.

The fertilizer N requirement would have been less on a morefertile, higher organic carbon

soil. Figure 9 illustrates that lower N fertilizationresulted in lower leaf N concentration

associated with N deficiency, which reduced assimilationand reduced biomass growth

(not shown) as well as fruit dry matter growth. At least120 kg N ha –1 was required to

sustain leaf N concentration at optimum target duringvegetative growth; however, even

at that rate, the leaf N concentration declined earlyduring fruit growth (Fig. 9), resulting

in a reduced yield (Fig. 8), although leaf N concentrationand yield could be sustained by

higher N application.

Figure 7 Simulated and observed number of tomato fruits perm 2 over time for the 1992 Bradenton

experiment (data from Scholberg et al., 1997).

7.2 Simulating tomato growth and yield response toirrigation under water-limited conditions

Industrial tomato production is sometimes done underwater-limited conditions. The

CROPGRO-Tomato model can be used to simulate irrigationstrategies for tomato

production (as done by Rinaldi, 2007; Rinaldi et al.,2007), and can also be used to simulate

transpiration and irrigation requirements. Figure 10illustrates total crop dry weight

Figure 8 Simulated fruit dry mass over time as affected byN fertilization (0 to 240 kg N ha –1 ) for the

1992 field experiment conducted at Bradenton, Florida.Observed tomato dry weight data are for

highly N-fertilized treatment of Scholberg et al. (1997).

Figure 9 Simulated leaf N concentration over time asaffected by N fertilization (20 to 240 kg N ha –1 )

for the 1992 field tomato experiment conducted on a sandysoil at Bradenton, Florida.

over time as affected by differential irrigation thresholds(cm depth of control and per cent

available soil water at which irrigation is applied) forthe 1992 tomato field experiment at

Bradenton, Florida. (To achieve the simulated water

deficit, rainfall was reduced to 30% of

the actual for all treatments, and the initial soil waterwas reduced for the two most severe

treatments.) The hypothetical water limitation reduced drymatter accumulation in total

crop (Fig. 10) as well as in fruit dry matter yield (Fig.11). Water deficit severely reduced

photosynthesis, transpiration, LAI, crop dry matter andfruit yield. Transpiration amounts

were 266, 217, 172, 127 and 57 mm for the five irrigationtreatments, respectively. The

model simulated earlier maturation under water deficit.These two figures are hypothetical

examples of water deficits that can be simulated with themodel, but further tests with real

experiments are needed.

8 Summary

The CROPGRO-Tomato model can be used by producers to managetheir tomato crop

in several ways: (1) predicting probable maturity date andyield, for a given particular

year weather pattern or prior long-term weather, (2)optimizing irrigation strategies based

on simulated transpiration water demand, (3) optimizingfertilizer N strategies, based on

simulated growth response to N fertilizer applications and(4) predicting fruit size and size

distribution relative to past weather experienced.Sustainability of production relative to

water and fertilizer N resources can be important forproducers. The CROPGRO-Tomato

model was used successfully by Rinaldi (2007) to evaluateirrigation strategies for field

grown processing tomato relative to long-term weather.Rinaldi concluded that the

model was a useful decision-support system to help farmersevaluate optimal irrigation

Figure 10 Simulated total crop dry weight over time asaffected by differential irrigation thresholds

(depth of control in cm, and per cent available soil waterat which irrigation is applied) for the 1992

tomato field experiment conducted at Bradenton, Florida.Observed dry weight data are for the well

irrigated treatment of Scholberg et al. (1997).

management strategy. In another application, Rinaldi et al.(2007) used the model to

evaluate optimal N-fertilization strategies for field-growntomato under differential water

management, with the goal of minimizing N leaching into thegroundwater while sustaining

good tomato production. These dual goals are important inmany tomato-producing areas

where the soils are sandy and are susceptible to N leachinginto ground water. See Boote

et al. (1996) for a review of the various uses andlimitations of crop models.


A new not yet public version of the model has beendeveloped by Jones et al. (2014) in

which a two-dimensional soil bed is simulated with plasticmulch and drip irrigation. This

version will enhance simulations of mulch-plastic-bed fieldtomato crops for the following

reasons: (1) drip irrigation is mechanistically simulatedwith Green-Ampt flow of water and

soluble fertilizer N in the water from the drip tape, (2)rainfall is shed by the plastic mulch,

thus minimizing rainfall-induced N leaching from the bedand yielding a more realistic crop

response to N applied for mulched tomato, (3) soilevaporation is minimized by the plastic

mulch portion of the bed, more correctly reproducing soilevaporation and transpiration

and (4) root growth patterns in the bed are morerealistically simulated (roots tend to

follow the provided water and fertility).

Another development in process is the parameterization andadaptation of the model

to simulate P deficiency (based on soil P test) andP-fertilizer application. This research is in

process with Brazilian colleagues, and will be available ina future DSSAT release in one or

two years. The P-response version of the model will beuseful in tropical and other regions

of the world where phosphorus deficiency is serious, andsoil testing is available.

Figure 11 Simulated fruit dry weight over time as affectedby differential irrigation thresholds (depth

of control in cm, and per cent available soil water atwhich irrigation is applied) for the 1992 tomato

field experiment conducted at Bradenton, Florida. Observeddry weight data are for the well-irrigated

treatment of Scholberg et al. (1997).

With some code modification, it may be possible to have themodel simulate as a single

stem greenhouse tomato, or to do model predictions ofsequential harvests of indeterminate

cultivars, in contrast to the present single harvest of

semi-determinate field cultivars.


• Description of the CROPGRO-Tomato model: Boote, K. J., M.R. Rybak, J. M. S. Scholberg and J. W. Jones. 2012.Improving the CROPGRO-Tomato model for predicting growthand yield response to temperature. HortScience 47: 1038–49.

• Overview paper on the DSSAT crop modeling software:Jones, J. W., G. Hoogenboom, C. H. Porter, K. J. Boote, W.D. Batchelor, L. A. Hunt, P. W. Wilkens, U. Singh, A. J.Gijsman and J. T. Ritchie. 2003. The DSSAT cropping systemmodel. European Journal of Agronomy 18: 235–65.

• Go to: www.dssat.org, for further information on DSSATcrop models, to download the DSSAT software along withCSM-CROPGRO-Tomato.

• Go to: www.agmip.org, for information on the AgriculturalModel Intercomparison and Improvement Project (AgMIP), aconsortium of international scientists using climate, cropand economic models to evaluate the effects of climatechange and climate variability on crop production and foodsecurity including economic consequences.

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2 Chapter 2 Optimizing yields in tomatocultivation: maximizing tomato plant useof resources

1 Introduction

Farmers and agronomists face the challenge of achievingsustainable production and

trade of tomatoes. To meet this objective, they must aimfor maximum efficiency in the

use of natural resources (water, carbon dioxide (CO 2 ) andsolar radiation) and agricultural

inputs (fertilizers, pesticides etc.). They must alsominimize the social and environmental

impacts of tomato production. To achieve these goals,proper understanding of both plant

physiology and plant production systems is required.

Our understanding of the relationship between cropproduction systems and yield

depends on our knowledge of basic plant biochemistry andphysiology. To show how

far this knowledge has progressed, an experiment assessingthe contribution of plant

physiology to the yield, published in the seventeenthcentury, is noteworthy. The Belgian

physician and alchemist Jean Baptista Van Helmont planted aseedling of willow tree

weighing about five pounds (2.25 kg) in a pot with 200pounds of soil (90 kg). This plant

was irrigated by rainwater or distilled water over thecourse of five years. After that period,

Van Helmont cut and weighed all the plant parts and notedthat the tree weighed 169

pounds (77 kg) while the soil had lost only two ounces (57g). He concluded that 164

pounds of wood, bark and roots had been produced from thewater.

The principles of photosynthesis were not known in VanHelmont’s time. We now know

that, on average, 96% of the dry matter of a plant iscomposed of carbon (45%), oxygen

(about 45%) and hydrogen (about 6%). These elements arenatural resources that go into

the plant via the stomata, the main channels for gas flowinto and of leaves.

The operation of the stomata affects photosynthesis,transpiration and respiration (Wong

et al., 1979). The stomatal opening chamber needs to beopen for the operation of these

major biochemical mechanisms, so that vegetable dry mattercan be produced efficiently.

Accordingly, this aperture is strongly affected byenvironmental conditions (Hetherington

and Woodward, 2003). To achieve sustainable production, itmust be ensured that the

stomata operate to allow the plant to acquire CO 2 (fromthe air). The plant must also be

able to acquire water and minerals from the soilefficiently. The plant can then use light

energy to produce 96% of vegetable dry matter (Zelitch,1975).

A plant’s absorption of CO 2 can be estimated using theliquid rate of CO 2 absorbed by

the plant’s leaf area. It is important to note that thecarbon absorbed will be used not only

for the production of dry matter of commercial interest,but also for the production of dry

matter for all parts of the plant and as a substrate in therespiratory process.

The harvest index indicates the ratio of dry matter ofcommercial interest in relation to

the total dry matter of the plant. Regarding to tomatoproduction, this is the production

of tomato fruits compared to the total production of drymatter by the plant. During

breeding, varieties having a higher harvest index areusually selected. Thus, commercial

tomato varieties have great efficiency in transforming CO 2into fruit.

Agronomists and farmers should use growing techniques whichensure that plants are

maximally efficient in absorbing and using CO 2 , water andnutrients. This will result in the

production of maximum dry matter in the form of fruit. Thewhole process of absorption

and efficient use of CO 2 , water and nutrients begins whenthe stomata open. It is therefore

reasonable to assume that by developing a tomato productionsystem which promotes

longer stomatal opening times in the plant canopy duringthe light period, we will be able

to reach higher yields. Notably, this increase in yieldwill not require extra investment in

agricultural inputs. This makes it a very promisingcandidate for ensuring more sustainable

tomato production. We call this system Opening StomataAgriculture (OSA).

The importance of the stomatal aperture for tomatoproduction can be shown by

considering the composition of a tomato fruit. The tomatofruit is composed, on average,

of 90% water and 10% dry matter. Ninety-six per cent of the

dry matter is composed of

carbon (C), hydrogen (H) and oxygen (O). Accordingly, in a100 g tomato fruit, 90 g will be

water and 10 g will be dry matter. In the 10 g of drymatter, 9.6 g is carbon (C), hydrogen

(H) and oxygen (O), and thus only 0.4 g is composed ofmineral constituents. Therefore,

the inflow of CO 2 and water (principles of ‘OSA’) accountfor 99.6 g (99.6%) of the 100 g

fruit that will be marketed. Accordingly, improvements instomatal conductance could not

only increase photosynthesis but also potentially increaseyield (Zheng et al., 2011; Franks

et al., 2009).

The opening of the stoma pore occurs through the movementof water into the guard

cells by a difference in osmotic potential. This differenceoccurs because of the movement

of solutes into the guard cells, reducing intracellularosmotic potential and resulting in the

movement of water from the apoplast to within the cellmedium (Roelfsema et al., 2001).

The process of opening and closing stomata pores, whichregulates the photosynthetic

process (Heuvelink et al., 2005), occurs in response tovarious biotic and abiotic factors as

well as to internal and external stimuli. The main goals ofthis process are to preserve the

internal water status of the plant and to absorbatmospheric CO 2 . Importantly, stomatal

conductance is positively correlated with growth and yield,even in different environments

(Condon et al., 2006).

In addition to the control of water loss, stomata directlyaffect CO 2 fixation in response

to environmental cues. Under field conditions, thispositive response between stomatal

conductance and yield might be modified by several factors,including interaction with

other plants or stresses to the plant. However, settingthis aside, the main factors that

affect opening and closure of stomata pores are soil wateravailability, light, CO 2 , relative

air moisture, air temperature and wind. Sections 2 and 3discuss these factors, and then

subsequent sections review how these factors may interact,the cultural practices that

can promote stomatal opening, methods for determining thewater status and then

transpiration rate of plants. The aim of the chapter is toprovide novel insights into

improving tomato yield by ensuring stomatal pores stay openfor longer during the light

period, and to consider the potential of using stomatalmovements in governing plant

growth and yield.

2 Factors affecting stomatal opening in tomato plants

2.1 Soil water availability

Soil is a three-phase system consisting of minerals,organic matter, water and air (Schjønning

et al., 2002; Tuli et al., 2005; Deepagoda et al., 2011).The liquid phase is the soil solution

that contains water and several important ions for plantnutrition. This fills a proportion of

the pore spaces in the soil.

In the natural environment, soil solution is retained atdifferent levels of strength,

depending on local water levels and soil pore size. Plantscan readily absorb water from

the soil when the moisture content is optimal for plantgrowth (field capacity), and this

water mostly comes from soil pores of intermediate size.When there is a reduction in soil

water content, only the solution retained in smaller soilpores or a thin film around soil

particles remains. There will then be competition betweensoil particles and plants for

the remaining water in these locations, until the soil’swater level reaches the permanent

wilting point (where the plant is no longer able to absorbwater and dies).

The amount of soil solution available to be used by a plantvaries according to soil

characteristics (texture, porosity etc.) and the plant(root distribution and depth). The water

available to the plants is the amount of water between thefield capacity (qCC) and the

permanent wilting point (qPMP) (Kirkham, 2005; Veihmeyerand Hendrickson, 1949).

The gaseous phase of soil occupies the pore space notfilled by the liquid phase. A well

aerated soil is very important for crop yield because theroots of plants require oxygen to

carry out their metabolic processes. Soil organisms alsoneed to respire and under poor

oxygen content, competition for oxygen between theseorganisms and plant roots may

occur. The transport of nitrogen and oxygen, which are

indispensable for plant growth,

occurs in the gaseous phase of the soil (Seyfried andMurdock, 1997; Smith et al., 2009;

Roberts et al., 2011).

Human activities interfere with an agricultural system,changing and affecting the

fundamental physical properties of the soil which affectthe development of plants and the

preservation of water resources (Klein, 1998). Changes thatoccur in the soil structure, as

evidenced by changes in its density, affect the soil’smechanical resistance to penetration,

distribution of soil pore sizes, water storage and solutionavailability to the plants (Klein,

1998; Camara and Klein, 2005a; Vieira, 2006).

Soils with physical characteristics suitable forcultivation have large amounts of solution

at water field capacity and appropriate air content forplant growth. The soil becomes a

limiting factor for crop production when subjected tointensive cultivation and the use of

heavy machinery, since these cause higher soil density dueto compacted soil (Hamza and

Anderson, 2005; Becerra et al., 2010; Tracy et al., 2011).

Soil compaction results in reduced soil porosity, aeration,total capacity of water

infiltration and hydraulic conductivity (Silva et al.,2009). Increasing soil density increases

the soil’s resistance to root penetration (Moraes et al.,2014). It is therefore associated with

limited root depth, and thus reduction in the effectivevolume explored by the roots for

water and nutrient uptake (Chen et al., 2014). Therefore,soil compaction challenges root

growth, resulting in the reduction of biomass and yield(Tubeileh et al., 2003; Ma et al.,

2013). It may also interfere with the opening and closingof the stomata.

The presence of water is detected by a plant’s roots, whichthen need to develop an

osmotic potential lower than that of the soil. This allowsthe roots to absorb the soil

solution, which always moves from a higher to a lowerpotential. The lower the osmotic

potential of the roots, the faster water will enter in theplant.

The absorption of water by the apoplast (xylem) accountsfor approximately 90% of the

water that enters the plant. The movement of water throughthe symplast (phloem) plays

a complementary role (Castro et al., 2005), allowing aerialparts of the plant to remain

hydrated.

The plant senses limited water supply through the roothairs. When this limitation

approaches drought status, there is signalling through theroots and up to the leaves.

Thus, by the transpiration flow, soil water levels triggerstomatal closure, to prevent

the plant from losing too much water (Flexas et al., 2002;Anjum et al., 2011). As the

stomata close, leaf transpiration and CO 2 assimilationdecrease, reducing the efficiency

of the mechanisms associated with photosynthesis, such aselectron transport, chlorophyll

content and enzymatic processes (Farquhar and Sharkey,1982).

The phytohormone abscisic acid (ABA) plays an importantrole, not only during fruit

development and ripening, but also during suboptimalconditions (e.g. in the presence

of biotic and abiotic stresses such as drought or highertemperature). It is the main

phytohormone responsible for stomatal closure (Bright etal., 2006; Jiang and Hartung,

2008), senescence (Finkelstein, 2013), and root elongation,and shoot etiolation (Luo

et al., 2014; Thole et al., 2014).

ABA also plays a central role in long distance signallingduring water limitation episodes

by controlling stomatal movements and thus retaining waterwithin the plant (Zhang and

Davies, 1991; Davies et al., 2002). It also coordinates thereduction of the water potential

in the roots in response to low water soil potential(Puertolas et al., 2013). Thus, under

these limiting conditions ABA maintains a small flow ofwater by root xylem towards the

leaves (Li et al., 2011; Wang et al., 2012; Correia et al.,2014.).

The production of ABA under water stress conditions showsthe plant’s ability to regulate

its metabolism. Production of ABA is triggered rapidly topreserve the water status of

plants and thus avoids desiccation. ABA is then rapidlydegraded and deactivated when

water stress is reduced, allowing the plant to reassumenormal growth and development

activities (Zhang et al., 2006).

Although our knowledge of ABA metabolism, signaltransduction and transport has

increased over the past few decades, the precise mechanismsby which ABA acts to

reduce the effects of water deficit still need to beelucidated. There is a growing body

of evidence that ABA mediates the radial K + transportthrough membranes, and this is

extremely important for normal physiological processes inplants (Roberts and Snowman,

2000).

ABA controls stomatal movement by mediating the input andoutput of potassium ions

(K + ) in the guard cells. This hormone increases cytosolicCa 2+ , which causes depolarization

of the plasma membrane and deactivates the K + channels,leading to K + efflux from the

guard cells and ultimately leading to stomatal closure(Ilan et al., 1994; Miedema and

Assmann, 1996; Schulz-Lessdorf et al., 1996). ABA can alsoregulate the turgor of the

guard cells by converting malate into starch, which isosmotically inactive (MacRobbie,

1998). Further evidence about the role of sucrose as anosmolyte mediating stomatal

regulation has been recently revisited (Daloso et al.,2016).

Our understanding of the mechanisms by which plants controland regulate their

metabolism to face limited water supply has progressedconsiderably. However, the

mechanism associated with the plant’s ability to sense

limitations in the water supply and

to close the stomata in order to preserve internal waterstatus remains rather unclear.

Nevertheless, it seems clear that in order to preventreductions in photosynthesis efficiency

as a response to stomatal closure, farmers shouldprioritize the growth of tomatoes in

deeper soils with enriched medium-diameter pores. This willhelp to ensure that plants

receive a greater and more regular supply of waterthroughout the entire plant, and should

thus prevent stomatal closure.

2.2 Light levels

Light provides not only the energy source forphotosynthesis but also a wealth of

information to optimize plant growth (Chen et al., 2004).In addition, light is one

important environmental factor involved in the control ofstomata movements. Two

signalling pathways, controlled by blue and red light, areinvolved in stomatal movements

(Shimazaki et al., 2007). Blue light is the major triggerfor stomatal opening, and two

families of blue light receptors, phototropins (phots) andcryptochromes (crys), regulate

this response additively (Chen et al., 2004; Shimazaki etal., 2007). Apart from this fact, the

main components in the signalling cascades that link theperception of blue light to the

opening of stomata remain largely unknown (Chen et al.,2012).

During the morning, which is rich in blue light, a plasmamembrane H + -ATPase present in

the guard cells is activated, resulting inhyperpolarization of the membrane and activation

of K + channels that transport this ion into the cells(Shimazaki et al., 2007). During the

afternoon, sucrose accumulates in the guard cells toreplace K + , keeping the osmotic

potential constant and the stomata open. Although sucrosehas long been proposed as

an osmolyte involved in guard cell movement (Tallman andZeiger, 1988; Vavasseur et al.,

2005), it was only recently that experimental evidence wasprovided for the functional role

of sucrose in guard cells other than its osmotic role.Sucrose breakdown in guard cells

seems to be directly involved in mechanisms able to induceboth stomatal closure (Kelly

et al., 2013) and opening (Daloso et al., 2015), suggestingnon-osmolytic functions for

sucrose in the regulation of guard cell movements. Furtherexperimentation is still required

to unequivocally determine the function of sucrose duringresponses to blue light.

It is important to mention that experimental evidence hasalready demonstrated that

just a short period of exposure to blue light is sufficientfor stomata opening (Lino et al.,

1985). Accordingly, it seems reasonable to assume that itis during the morning that a

plant’s stomata could be open for longer, with consequentenhanced CO 2 fixation capacity,

as long as there is no further limitation due to otherfactors such as water availability in

the soil, relative humidity, CO 2 concentration, hormones,

temperature and wind, among

others (Zeiger, 1984).

Although red light also influences the stomatal opening, ahigher intensity and duration

is required to gain the same effect (Roelfsema et al.,2002; Mott et al., 2008). This opening

process occurs mainly by reducing the intercellular carbonconcentration (C i ) as a result of

the stimulation of photosynthesis by red light in themesophyll cells (Hanstein et al., 2001),

leading to increased consumption of CO 2 . Remarkably, thered light response of stomatal

conductance is independent of the photosynthetic activityof the guard cells or the

underlying mesophyll. Moreover, when leaves were treatedunder a constant intracellular

CO 2 concentration, red light still stimulated the openingof stomata (Messinger et al.,

2006).

Compelling evidence has demonstrated a synergistic effectwhen blue and red lights

are combined. It was demonstrated that in the presence ofboth blue and red lights,

stomatal opening is larger than the sum of the effect ofeach light separately (Shimazaki et

al., 2007). The components involved in this combinedresponse remain largely unknown.

Although how the light signals are transduced from thevarious photoreceptors is not

well understood, several transcription factors in thenucleus are known to be involved

in the regulation of the stomatal aperture under lightconditions. It is also clear that the

process of stomatal opening and closing depends on both theamount and quality of light

supplied to the leaf blade. Light should therefore bepromoted, whether by adjusting

plant population, by staking or by selecting cultivarswhose higher leaves are also shorter,

thus ensuring that light reaches all of the plant canopy.

After many decades of studies into stomata responses tolight, we have increased our

knowledge about the photoreceptors and some downstreamcomponents involved in the

regulation of stomatal aperture in response to lightsignals. However, much more needs

to be explored in the years to come in order to increaseproductivity. We strongly believe

that the maintenance of open stomata for longer periodsduring the light period should

help to increase crop yield, particularly in plants such astomato, where populations and

crop systems can be easily manipulated. In broad terms,light can be assumed as one of

the major environmental factors that might ultimately limitbiomass production and crop

yield. Further studies aimed at the maximization ofphotosynthesis will open new avenues

to engineer stomata activity and to allow plants to enhanceyield.

2.3 CO 2

An annual increase of approximately 2 mmol mol −1 has beennoted in the CO 2 concentration,

[CO 22 ], of atmospheric air. This resulted in the [CO 2 ]of the air exceeding 400 mmol mol −1

in 2014. If [CO 2 ] continues to rise at the same rate, itwill exceed 700 ppm by the end of

the century (IPCC, 2013).

High [CO 2 ] normally favours crops with a C 3 carbonfixation metabolism, such as

tomato. In such plants, it causes an increase in the netphotosynthesis rate and significant

enhancements in total dry biomass. The enrichment of theatmospheric air with carbon

dioxide can ensure a higher influx of CO 2 into the plant,increasing C i and resulting in a

better efficiency in liquid carbon assimilation rates.

Two main reasons explain this increase in both rate andphotosynthetic efficiency:

(i) there is a substrate limitation under the current [CO 2] conditions and an increase in

this concentration may result in higher rates ofcarboxylation reactions of Rubisco, and

(ii) these increases in [CO 2 ] will lead to reduction inthe Rubisco oxygenation reactions,

reducing losses of CO 2 and energy cost associated withphotorespiration mechanisms

(Ainsworth and Rogers, 2007). However, it is important tostress that photorespiration

allows the recovery of carbon atoms lost during Rubiscooxygenation. Photorespiration

is therefore a highly efficient metabolic repair system(Bauwe et al., 2012; Linster et al.,

2013).

The photorespiratory carbon flow is exceptionally high in C3 plants and thus about half

of the photorespiratory CO 2 is not reassimilated but lostto the environment, resulting in a

considerable difference between gross and netphotosynthesis. This is arguably the main

reason why photorespiration has been a prime target forcrop improvement over recent

decades (Ort et al., 2015). Although increments in thegrowth of Arabidopsis thaliana

plants under well-controlled conditions have been achievedby introducing two different

photorespiratory bypasses via metabolic engineering (for areview, see Peterhansel et al.,

2013), it remains to be tested whether this would result insimilar increments under field

conditions.

Increments in CO 2 are associated with increases in netphotosynthetic rates, biomass,

sugars, organic acids, firmness, seed production andefficiency in the use of light, water

and nutrients, as well as in changes in stomatalconductance (Moretti et al., 2010). In the

same vein, under high CO 2 concentrations (700 ppm CO 2 ),there is an increase in the net

carbon assimilation rate, a decrease in stomatalconductance, a reduction in the osmotic

potential and an increase in leaf water potential in thestages of flowering and fruiting, as

well as higher fruit production. However, there is adecrease in the content of phenols,

flavonoids, soluble solids and titratable acidity (Mamathaet al., 2014). High CO 2 results

also in a higher number of tubers per plant in potatoes(Miglietta et al., 1998). In tomato

plants, increased CO 2 resulted in lower respiratoryrates, fruit ripening, citric and malic

acid content and sugar concentration (Da Matta et al.,2010).

Elevated CO 2 can reduce the photosynthetic capacity ofsome species, a phenomenon

called acclimatization, which is usually related tonutrient limitation (Da Matta et al., 2010).

In C 3 species, such as the tomato, the most pronouncedand universally observed response

is the accumulation of carbohydrates in the leaves, causingphotosynthetic acclimation,

which is attributed to the lower carboxylation rate ofRubisco (Da Matta et al., 2015).

This indicates that the results observed under specificelevated CO 2 conditions should

be treated with caution, and that further studies are stillrequired to fully understand the

complexity of a plant’s response to elevated CO 2 , beyondsuch metabolic and growth

responses.

2.4 Temperature

Temperature stress can be defined as changes in the ambienttemperature which take it

above or below an optimum range for a period, which aresufficient to cause damage to

the growth and development of the plant. This clearlydepends on the intensity, duration

and rate of temperature alterations (Wahid et al., 2007).

High temperature can inhibit the photosynthetic process,even before other symptoms

are detected (Berry and Björkman, 1980). Interestingly, ithas been suggested that

higher temperatures reduce net carbon gain by increasing

plant respiration more than

photosynthesis. In fact, however, the light-saturatedphotosynthetic rate of C 3 crops such

as tomato and rice is at a maximum for temperatures fromabout 20–32°C, whereas total

crop respiration shows a steep non-linear increase fortemperatures from 15 to 40°C,

followed by a rapid and approximately linear decline(Porter, 2005).

It is common knowledge that cultivation under highertemperatures can reduce plant

production (Zhang, 2010). Nevertheless, high temperaturescan also increase the number

of stomata on the leaves which can be seen, since onestrategy a plant uses to respond

to higher temperatures is to increase leaf transpiration tolower its internal temperature

(Zhang et al., 2014). Furthermore, under higher thanoptimum temperatures, there is an

increase in stomatal conductance, transpiration andabsorption of CO 2 . Nevertheless,

photosynthesis is reduced, because high temperatures damagethe photosystem, causing

a reduction in the activity of the Calvin cycle, which mayvary in intensity between different

cultivars (Camejo et al., 2005).

The overall reduction in photosynthesis suggests that themost significant effect of high

temperature is on photosynthetic function. As a consequenceof global warming, plants will

have to face more severe and more frequent periods of hightemperature stress. Although

such high temperature stress affects the whole plant,

sexual reproduction is one of the

processes most sensitive to heat stress, leading toconsequences for flower development

and number, and pollen production and viability, which inturn lead to reduced seed set

and yield (Prasad et al., 2006; Das et al., 2014).Reproduction has also been recognized as

the phase most susceptible to heat stress in cereals(Monterroso and Wien, 1990; Barnaba

et al., 2008) and vegetables (Erickson and Markhart, 2002),with male reproductive stages

being more sensitive to heat stress than female orvegetative stages of growth (Sakata and

Higashitani, 2008).

In tomato plants it has been demonstrated that the majoreffect of high temperature

on the pollen development process is the disruption ofcarbohydrate metabolism and

proline translocation (Sato et al., 2006). This leads to areduction in starch and sugar

concentration in mature pollen grains, with a subsequentloss of pollen viability (Pressman

et al., 2002). The end results are fruit set failure andcrop losses at high temperatures.

Interestingly, it has been demonstrated that heat-toleranttomato genotypes differ from

heat sensitive ones in their ability to accumulate starchand soluble sugars during pollen

development under heat stress conditions (Firon et al.,2006). As a consequence, under

high temperature, heat-tolerant tomatoes produce viablepollen and high fruit set (Firon

et al., 2006). The precise mechanism by which plants manage

to maintain the appropriate

levels of starch and soluble sugars under heat stress, thusallowing higher crop production,

is not yet understood.

It is important to stress that whilst changes intemperature impact all plant cells and

require an organized cellular response, the effects of andresponses to high temperature

in sexual organs are different from those in vegetativetissues in several ways. This could

be related to the specific physiological characteristicsneeded for developing pollen and

supporting fruit tissues, or it could be related to theeffects of reproductive processes,

such as reactive oxygen species accumulation andcarbohydrate starvation.

Selection and breeding of plants with increased toleranceto high temperature

stress seems highly promising as a way to mitigate adverseeffects of increasing global

temperatures and allow maintenance of or increments in cropyield.

2.5 Relative air humidity

Plants grown under high relative air humidity (RAH) willkeep their stomata open longer

than plants in environments with moderate or low humidity(Torre et al., 2003; Nejad and

van Meeteren, 2005). There is evidence that plant hormonesplay an important role in the

response of the stomata under high humidity conditions(Aliniaeifard and van Meeteren,

2013), but the precise mechanism remains to be elucidated.

In plants grown under high RAH for long periods, thestomata become less sensitive to

the signals that normally induce their closure, such asdarkness, abscisic acid, high CO 2

concentration and water stress (Tower and Fjeld, 2001; Arveet al., 2013).

Interestingly, in tomato plants, a short period of exposureto high RAH is sufficient to

keep the stomata open, even during the night (Arve andTower, 2015). High air humidity

also leads to less transpiration even with the stomata open(Arve and Tower, 2015), since

the gradient allowing transpiration is reduced.

The stomatal conductance of tomato plants under high RAHconditions is directly related

to the interaction between ABA and ethylene. Ethylenestimulates stomatal opening, while

ABA has the opposite effect. Thus, plants growing underhigh RAH have a low ABA to

ethylene ratio, while those growing under moderate or lowRAH, have a higher proportion

of ABA (Arve and Tower, 2015), directly impacting stomatalresponses.

The rapid growth of internodes is another effect that isusually related to high RAH, and

this results in greater plant height and the development ofadventitious roots, as a result

of the ethylene formed in this condition (Arve and Tower,2015). Importantly, this is not

directly associated with higher biomass production andtherefore caution must be taken

when considering these results.

The reduction of transpiration in high RAH also results in

greater efficiency of water use.

However, this condition may reduce nutrient absorption,leading to nutritional deficiencies.

This is a particular concern for less mobile nutrients suchas Ca and Mg (Suzuki et al., 2015).

2.6 Wind

Moderate winds can draw away the accumulated moisture inthe abaxial part of the leaf,

and thus increase transpiration. By contrast, strong windsmay reduce transpiration by

mechanical movement and thus help cool the leaves (Castroet al., 2005).

The influence of the wind on stomatal conductance andtranspiration rate is also related

to the RAH. In plants grown in an environment with moderateRAH, wind increases the

transpiration rate. However, when the RAH is high, theeffect of the wind is virtually nil, as

the air present at the boundary layer is saturated withmoisture and will be replaced by

another layer of air with high humidity (Carvalho et al.,2015).

3 Interaction of stomatal opening factors

The process of opening and closing of stomata is highlycomplex and results from the

interaction of all the factors mentioned above. Afavourable condition for stomatal

opening, high relative humidity, for instance, has noeffect if the plant is under soil drought

stress. In addition, the wrong conditions with respect toone of these factors can lead to

stomatal closure. For example, soaked soils may result inanaerobic conditions causing the

death of roots and consequently reducing the wateravailability to the plant.

Other factors may also influence stomatal opening. Stomatapores also provide a

natural entry site for potentially harmful microbes. Toprevent microbial invasion, stomata

close upon perception of microbe-associated molecularpatterns. This is an important

layer of active immunity at the pre-invasive level. Thesignalling pathways leading to

stomatal closure which are triggered by biotic and abioticstresses employ several

common components, which have been expertly reviewedelsewhere (Sawinski et al.,

2013). Infestation of plant roots with endoparasiticnematodes such as the root-knot

nematodes, of the genus Meloidogyne, makes plants moreprone to water stress, and

they also show symptoms of nutrient deficiency andpremature senescence (Bartlem et al.,

2014), resulting in a water deficit even in soils with highwater availability. Needless to say,

a better understanding of how nematode infestation impairsroot function and reduces

yields and product quality should be pursued.

Applying the concept of sustainable agriculture, where theobjective is to maximize

the efficiency of the use of water, light and CO 2 , it isof pivotal importance to integrate all

factors leading to stomatal opening in order to optimizethe environmental conditions for

the maximization of plant growth and production. This isobviously not an easy task, since

for the most part we have little or no control overenvironmental factors. However, a deeper

understanding of the factors involved in stomatalregulation may allow further advances in

our understanding of how guard cells play their role toensure growth optimization.

The soil needs to have high water-holding capacity, and thewater must be easily accessible

to the plants. Deep soils with many soil pores of mediumdiameter, allowing higher water

and O 2 retention, are desired. Under these conditions,roots will be able to explore deeper

layers and larger areas, increasing their capacity toabsorb water and nutrients.

Considering the climatic factors, the ideal solution wouldbe an environment with

high availability of light and high [CO 2 ], moderatetemperature (25–30°C) and a RAH of

approximately 70%. These would be the optimal conditionsfor higher stomatal opening

and assimilation of CO 2 , without stimulating excessivetranspiration, which can lead to low

efficiency in water use.

We are aware that there is a wide variation in thesefactors under field conditions, which

can compromise the success of the crop. Understanding thegenetic factors involved

in a plant’s response to these factors will allow plantbreeders to find the most suitable

genotype for the conditions in which they intend to growthe plants. However, achieving

this understanding will take much more time and greaterresearch efforts than are needed

for the manipulation of cultural practices to cope withthese conditions, such as plant

population, and pruning and staking systems. In the nextsection we review how such

cultural practices can increase or inhibit a plant’s use ofresources.

4 Cultivation practices to maximize tomato plant use

of resources

4.1 Plant population

Water, light, [CO 2 ], temperature and RAH are importantfactors in determining the final

plant population. Normally, higher availability of theseresources enables higher possible

numbers of plants per area.

The plant population directly affects the leaf area index(LAI), which is the leaf area of a

plant per unit of ground surface (m²/m²). Accordingly, theinterception of solar radiation

is approximately 90% when the LAI is close to 3. Compellingevidence has demonstrated

that increase in light interception and productivity gainis minimal and even difficult to

experimentally detect above this value (Heuvelink, 1996).

In greenhouses production it is common to allow thedevelopment of lateral buds in

crops growing at the arrival of summer. This increases theplant density at the time when

light availability is highest (Heuvelink, 2005). Duringwinter, when the amount of light is

lower, the spacing between plants should be larger toincrease light interception and thus

reduce self-shading inside the canopy.

Similarly, fewer plants per area must be recommended forconditions of high relative

humidity, since such conditions favour diseases. A lowerplanting density allows more

air renewal along the rows and greater light penetrationthrough the canopy, reducing

the incidence of diseases and increasing transpiration,water and nutrient uptake, and

assimilation of CO 2 and so ultimately increasing growth.

Increasing the number of plants per area results in higheryields, but reduces both

production per plant and fruit size (Ara et al., 2007;Maboko et al., 2011). The optimization

of plant spacing results in better use of water, light andnutrients without significantly

affecting the fruit size (Ismail et al., 2014). With thedensity of the tomato crop at 2.5 plants

per square meter, the yield increases, with a large fruitproduction by 227 and 212%,

respectively (Almeida et al., 2015).

4.2 Pruning

In the cultivation of indeterminate growth type tomatoes,it is common to cultivate the

tomato plant with one or two stems, eliminating theremaining side shoots. The cultivation

of plants with two stems increases the LAI and productionper plant, but reduces the

weight of the fruit (Ambroszczyk et al., 2008; Maboko etal., 2011).

Under high light conditions, it is possible to increase thenumber of stems as an

alternative to increasing planting density, reducing thecosts of seeds and seedlings.

Under these conditions, larger numbers of stems reduce windamong plants and increase

the humidity along the canopy. This technique is highlyrecommended for areas with

high temperatures and light levels, because the hightemperatures normally reduce RAH.

However, in places with high air humidity high plantdensity is not recommended because

it both reduces transpiration, thus further raising thehumidity, and can also increase the

incidence of diseases.

The removal of young leaves to increase dry matterpartitioning to the fruit is also a

common practice, especially in greenhouses. However, thistechnique can reduce the LAI

and negatively influence the yield (Xiao et al., 2004).

The removal of lower leaves is another technique commonlyused, especially in

greenhouses, to reduce the RAH, increase aeration, andreduce pests and diseases (Silva

et al., 2011). The leaves are removed below clusters wherethe fruits have been harvested.

However, when too many leaves are removed thissignificantly reduces leaf area and the

LAI, and so light absorption and yield are also reduced(Kim et al., 2014).

4.3 Staking methods

Staking tomato plants is common in cultivation for thefresh market, especially in countries

like Brazil and India, and also under greenhouseconditions. Staking aims to avoid contact

between the fruit and the ground, and can directlyinfluence the microclimate throughout

the plant canopy.

The main staking methods used in Brazil are traditional orinverted ‘V’ and vertical. In

the traditional method the plants are tied to stakes(bamboo) arranged obliquely to the

ground so as to form an inverted ‘V’ between twoconsecutive rows (Wanser et al., 2007).

In this system, a chamber is formed under the inverted ‘V’,which reduces the incidence

of radiation and wind and increases the RAH, creating anunfavourable environment for

photosynthesis.

In the vertical staking method, plants are vertically tiedto tutors (bamboos or strings),

increasing light interception and ventilation and reducingthe RAH throughout the plant

canopy (Wanser et al., 2007).

A new growing tomato system, the Viçosa System, hasrecently been proposed in Brazil

(Almeida et al., 2015). In this system, plants aretransplanted at 0.2 m and 2 m between

plants and rows, respectively. The plants are staked withstrings inclined at approximately

75º to the ground. They are inclined to both sidesalternately in a real ‘V’ shape, from

a top view. This ensures a higher plant density once thelight and photosynthesis

interception conditions are optimized, as there is greaterlight interception and higher

exposure to moderate wind, reducing the RAH and renewing

the concentration of CO 2 .

This method is suitable for places where there is no waterlimitation in the soil and there

is high RAH.

In places where the RAH is low, the ideal method is to growplants in conditions that

increase the RAH over the canopy, such as the inverted ‘V’staking system. This increases

the RAH among the plants, favours the stomata opening,reduces transpiration, water

absorption and enables assimilation of CO 2 .

5 Evaluation of plant water status

The following methods can be used to evaluate stomatalopening or transpiration: sap

flow, water balance in the soil, stomatal conductance,water potential in leaves and leaf

temperature (Trentin et al., 2011).

Transpiration is one of the main factors that determinesthe leaf temperature (Leuzinger

et al., 2010). It is reduced when subjected to waterstress, leading to an increase in leaf

temperature through the absorption of solar radiation(Gontia and Tiwari, 2008; Wang and

Gartung, 2010). Therefore, leaf or canopy temperature canbe a good indicator of water

restriction and stomatal conductance.

Several water stress indices have been developed usingtranspiration and leaf

temperature, which rely on the difference between thetemperature of the culture and

that of air to estimate the severity of the water stress(Testi et al., 2008; Lebourgeois et al.,

2010).

The crop water stress index is commonly used, and it isable to register higher and

lower temperatures. A higher temperature result from thismethod indicates that the crop

is under water stress and not transpiring, while a lowertemperature result corresponds to

a well-irrigated crop without limits on transpiration. Theresults are determined from the

canopy, air temperature and vapour pressure deficit (Zia etal., 2012).

Leaf or canopy temperature can also be measured throughinfrared thermometry, which

detects the thermal radiation emitted by the surface of theleaves (Mn and Mm, 2008).

Thermal cameras provide the temperatures of multiple leavesin a single image. This can be

used as a non-destructive method for estimating stomatalconductance (Jones et al., 2002).

Alternatively, the temperature difference between theleaves in the canopy can be

used to estimate water stress and stomatal closure. Thehigher the temperature variation

along the canopy, the higher the level of stomatal closureand the lower the stomatal

conductance (Jones et al., 2002).

The leaf temperature may be 1°C to 4°C lower than theambient temperature when

transpiration occurs under optimal conditions. Under waterstress conditions, transpiration

is reduced and the leaf temperature may reach 4°C to 6°Cabove ambient temperature.

Ramírez et al. (2015) reported that in tomato plants grownunder water stress, the difference

between leaf and ambient temperature was �1.18 to 9.71°C,but when tomatoes were

grown under no water limitations, the difference intemperature ranged from �6.29

to �2.98°C.

6 Future trends and conclusion

Despite of the knowledge accumulated during recent years,building on newly available

genetic resources and specific analyses of guard cellmetabolism, our understanding of

stomata responses to environmental factors remainsincomplete. Molecular and genetic

aspects of the regulation of this highly specialized celltype are being elucidated, but the

translation of this knowledge from model plants to cropsgrowing under field conditions

remains a challenge.

We cannot currently exclude the possibility that genotype ×environment interactions

will impact our understanding. That being said, theapplication of specific agronomical

practices coupled with molecular and ecophysiological toolsmay provide considerable

information concerning the regulation of stomata, and thismay allow ‘Opening Stomata

Agriculture’ to become a regular practice under fieldconditions. In this scenario, we

posit that coupling the best practices with respect toplant population, irrigation system

and growth system with genetic material recommended forspecific places will be highly

pertinent to crop science. This should provide excitingopportunities to both researches

and to farmers in the form of improved economic yields.

The evidence presented here suggests that a combination ofthe correct choice of

agronomical practices and the best genetic material shouldbe used to create significant

increases in crop yield.

7 Acknowledgements

The author would like to thank the Brazilian ScientificAgencies: CAPES, CNPq and

FAPEMIG.

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3 Chapter 3 Improving water and nutrientmanagement in tomato cultivation

1 Introduction

Although the US Supreme Court ruled in its decision in Nixv. Hedden (149 U.S. 304,

1893) that for trade purposes, tomato should be classifiedas a vegetable, botanically it

is a fruit that was recently renamed Solanum lycopersicum(L.) after long being identified

as Lycopericum esculentum (Mill.). Tomatoes of many genetic(open pollinated, hybrid

or transgenic), growth-habit (determinate, indeterminate orcompact), fruit-shape (round,

oblong, saladette, grape, cluster or ribbed) and fruitcolour (red, yellow, orange, green,

purple or brown) types are produced worldwide in openfields, greenhouses, conventional

or organic systems. Tomato cultivation includes varietyselection, fertilization and irrigation

management (Freeman et al., 2016), pest and diseaseidentification and control (Jones

et al., 2014), harvesting and grading (USDA, 1997), andpostharvest handling (Sargent

et al., 2014). Today’s agricultural practices used fortomato production need to (1) fulfil

the hydric and nutritional requirement of the crop foroptimal production, (2) consider

the environmental impact of production and (3) offernutritious and safe tomato fruits to

consumers.

Because of the variety of production methods, this chapterfocuses on irrigation and

fertilization practices for field production of

conventionally grown round (‘fresh-market’)

and processing (‘Roma’) tomatoes. It also presents the mainUS environmental regulations

that apply to irrigation and fertilization management,together with related food-safety

issues. Progress in irrigation and fertilization researchcan only affect field-production

practices through knowledge and technology transfers;hence, this chapter finally describes

challenges and successes in improving water and nutrientmanagement practices through

University-mediated grower education.

2 Overview of tomato production systems

Tomato average consumption in the United States in 2011 was45 and 145 kg/person

of fresh and canned tomatoes, respectively (USDA, 2015).When compared to 39 other

fruits and vegetables, tomatoes provide the highestrelative contribution in vitamin C,

lycopene and other natural antioxidants to the human diet(USDA-ARS, 2016; Simonne et

al., 2007a). These phytochemicals are associated with areduction in the risks of incidence

of cancer and cardiovascular diseases (Simonne et al.,2011). A medium-sized tomato

provides 40% of the recommended daily allowance of vitaminC and 20% of vitamin A

(Sargent et al., 2014; Simonne et al., 2011; USDA-ARS,2016). One medium-sized tomato

contains 25 calories and provides dietary fibre (USDA-ARS,2016).

The two largest tomato-producing countries in the world areChina and the United

States (http://faostat3.fao.org/browse/Q/QC/E). Nationally,Florida ranks first in fresh

market tomato production with a value of $437 million inthe 2014 season (USDA,

2015). In 2014, Florida had the largest fresh-market tomatoacreage in the United States

with nearly 16 000 ha harvested and an average yield ofnearly 30 000 kg/ha resulting

in almost 500 000 tons of tomato fruit produced (USDA,2015). As the second largest

tomato producer, California produced 30% of the USfresh-market tomato acreage with

nearly 15 500 ha harvested and a value of $304 million in2014 (USDA, 2015). Currently,

California also produces 94% of the processing tomatoes inthe United States with nearly

130 000 ha harvested, valued at $918 million in 2014 (USDA,2015).

In the United States, tomato varieties are typically hybridand are grown using one of

two production systems: bush (non-staked) or upright(staked and tied) methods. The

bush method is used in most processing-tomato plantings (LeStrange et al., 2000). Bush

tomatoes are grown in a single row with 0.40 m in-rowspacing and plant populations of

nearly 13 000 plants/ha. This industry uses determinatetomato varieties, which cease their

growth when fruits set on the apical meristems. Fruits maybe harvested manually once or

twice at the mature-green stage (Le Strange et al., 2000)or once-over mechanically when

90% of the fruit is ripe (Hartz et al., 2001; Geisseler and

Horwath, 2013).

In Florida, tomatoes are typically grown upright, in thefall, winter and spring

(transplanting dates between August and March) using raisedbeds, polyethylene mulch,

transplants, drip or seepage irrigation (described later),staked, and tied with four strings.

Most of the production occurs on sandy soils with lowwater-holding capacity (10%, v:v)

and low organic-matter content (�1.5%). The majority of theround and Roma-type tomato

varieties grown are determinate, and are commonlyhand-harvested up to 3 times at the

mature-green stage and sometimes once more at the coloredstage (Ozores-Hampton et

al., 2012) with specific criteria for size, shape, colour,and defects (USDA, 1997).

Mature-green tomato fruits are classified as green;however, the fruits are at physiological

and horticultural maturity. The ripening process ofmature-green tomatoes is completed

by exposing the fruits to exogenous ethylene. Ethylene is aplant hormone that is applied

to tomato fruits to promote rapid and uniform ripening(Sargent et al., 2014). Tomato

boxes of mature-green fruits are placed in ripening roomsat air temperatures of 19–21°C,

85% to 95% relative humidity, and 150 mg/L of ethylene gas.Tomato fruits are exposed

to ethylene gas until the desired colour stage is achievedat which point the tomato fruits

may be shipped or re-packed. These tomatoes are sold wholefor fresh market or used in

the food service industry whole, sliced or cubed.

Plant population in tomato fields depends on bed spacing(the distance between

the centres of two adjacent raised beds), plant spacing(the distance between two

adjacent plants) and the presence of unplanted rows formachinery traffic and harvest.

These spacings are determined by the machinery and thetransplanting wheel used. For

example, a tomato field with beds spaced 2.0 m apart has 10000/2 = 5000 m of row.

Moreover, drive rows are left unplanted typically every sixrows. In this example, the field

has 10 000/2 x 6/7 = 4286 m of row (and 714 m of driverows). Hence, 6/7 (or 86%) of the

field surface are planted in tomato in a commercial field.Within each row, tomato plants

are spaced 0.40–0.60 m apart (for larger and smallergrowth-habit plants, respectively)

which create plant populations of 3333 (calculated as5000/1.5) and 2500 (5000/2) for

fully bedded fields, and 2857 (5000 x 6/7/1.5) and 2143(5000 x 6/7/2) plants per planted

hectares for fields having a drive row every sixth row,respectively.

When plant populations, irrigation and fertilizer ratesused in tomato production are

reported in the literature, ‘1 ha’ represents the surfaceof a 1-hectare field (10 000 m 2 ) and

‘1 HA’ represents the length of bed in a 1-hectare fieldplanted at standard bed spacing

(5000 m of row). Using the planted rows (HA) concept forirrigation and fertilizer rates allow

for the correct rate adjustments when beds are establishedat bed spacings other than the

standard bed spacing. Water and nutrient management oftomato consists in managing

length of row, not field surfaces.

3 Environmental regulations affecting tomato productionin the United States

3.1 Federal regulation

In response to the public awareness of environmentalissues, section 303(d) of the US

Clean Water Act (US Congress, 1977) required that statesidentify impaired water bodies

and establish Total Maximum Daily Loads (TMDLs) forpollutants entering these water

bodies. Best Management Practices (BMP) are defined asspecific cultural or structural

practices aimed at reducing the negative environmentalimpact of production while

maintaining or increasing productivity. In short, BMPs aimat keeping water and nutrients in

the root zone (Simonne et al., 2009). Despite some growerreluctance to new regulations,

mounting evidence exists worldwide that the production andenvironmental constraints

are compatible (Singh and Ryan, 2015). The role of thestates is to define how the Clean

Water Act was to be implemented at the local level.

3.2 State regulation: the Florida example

In 1987, the Florida legislature passed the Surface WaterImprovement Act requiring

the five Florida water management districts to developplans to clean up and preserve

Florida lakes, bays, estuaries and rivers. In 1999, theFlorida Watershed Restauration Act

(Florida Senate, 1999) defined a process for thedevelopment of total maximum daily

loads (TMDL). A TMDL represents the quantity of a pollutanta water body can accept and

still have its water quality parameters consistent with itsintended use. Based on the water

body, the pollutants may be a nutrient [typically nitrogen(N) or phosphorus (P)], an organic

compound or a microorganism.

The Florida Department of Agriculture and Consumer Services(FDACS) adopted by

rule 5M-8 the first version of the ‘Water Quality andQuantity Best Management Practices

for Florida Vegetable and Agronomic Crops’ manual in 2005and an updated version

in 2015 (FDACS, 2015). Jointly developed by professionalsfrom FDACS, the University

of Florida, the water management districts and vegetableindustry representatives, this

manual outlines all the BMPs that growers may implement.Agronomic and vegetable

crops growers officially join the BMP programme by (1)developing a BMP plan for their

land and (2) signing a Notice of Intent (NOI) to implementBMPs. Growers with a signed

NOI receive a presumption of compliance with water qualitystandards and are eligible for

cost-share programmes (FDACS, 2015).

Since the late 2000s, the Florida Department ofEnvironmental Protection (FDEP) has

developed and approved Basin Management Action Plans

(BMAPs; http://www.dep.

state.fl.us/water/watersheds/bmap.htm). BMAPs are theblueprint for restoring impaired

water bodies by reducing pollutant loads to meet the TMDLs.Each BMAP includes a

comprehensive set of strategies such as permit limits onwastewater facilities, urban and

agricultural BMPs, conservation programmes, financialassistance and revenue-generating

activities for all the land uses in a watershed. Inwatersheds with adopted BMAPs,

agricultural producers either must implement FDACS-adoptedBMPs or must conduct

water quality monitoring prescribed by FDEP or the watermanagement districts.

In 2016, the Florida Legislature passed comprehensive waterpolicy legislation (adopted

by the Florida Senate as SB 552 and named the FloridaSpring and Aquifer Protection Act)

that sets water-flow levels for Florida’s freshwatersprings and seeks to develop verification

of the application of BMP plans in watersheds with BMAPs.BMAPs will include the

construction of water projects, water monitoringprogrammes, and the implementation,

verification, and enforcement of BMPs within thesewatersheds. The BMAPs will include

5-, 10- and 15-year measureable milestones towardsachieving the TMDL for those water

basins within 20 years.

3.3 Applying environmental regulation to field production:Best Management Practices (BMPs)

The BMP manual for agronomic and vegetable crops adopted

the fertilizer and irrigation

recommendations of the University of Florida for tomatoproduction (Freeman et al.,

2016). These recommendations consist in base fertilizerrates and supplemental fertilizer

applications. Supplemental fertilizer applications areallowed by the BMPs after each

qualified leaching rain event, which are defined as rainevents of 7.5 cm in 3 days or 10 cm

in 7 days. However, when vegetable plants are small, asingle-day rain event of 2 cm may

be enough to push soluble fertilizer below their root zone(Hendricks et al., 2007).

The ‘first-generation BMPs’ consisted of a multitude ofapproaches that included

fertilization plans and irrigation schedules (FDACS, 2015).The ‘second-generation BMPs’

intensely focuses on water and nutrient management andinclude controller-based, real

time irrigation schedule (Cardenas-Laihacar and Dukes,2010; Zotarelli et al., 2008a,b),

low-pressure drip-irrigation (Poh et al., 2011a,b), the useof the Soil Phosphorus Storage

Capacity Index to predict the risk of P loss outside theroot zone through leaching or erosion

(Rice et al., 2013), controlled-release fertilizers (CRFs;Guertal, 2009; Morgan et al., 2009;

Simonne and Hutchinson, 2005), amendments that increasesoil water-holding capacity

such as biochar (Singh et al., 2010; Biederman and Harpole,2013), polymers (Bavernik,

1994), or zeolites (Ming and Allen, 2001; Sepaskhah andYousefi, 2007), and amendments

that increase soil organic matter content such as manures(Ulén,1999), compost (Hepperly

et al., 2009) or cover crops (Hartwig and Ammon, 2002;Tonitto et al., 2006).

4 Changing approaches to water and nutrient management:from optimizing production to optimizing input efficiency

4.1 The traditional approach and its limits

The study of tomato plant response to irrigation andfertilization has traditionally been done

using rate studies (Dumas, 1990; Hochmuth and Hanlon,2014). In these studies, treatments

cover a range of rates and response variables (most oftenyield, grade distribution, shoot

height or fruit quality parameters such as pulp pH, solublesolid content, or titratable

acidity) are measured. Rate is considered a continuousvariable and the statistical analysis

of these trials is done using regression analysis. Linearor quadratic orthogonal contrasts

may also be used to determine trends; however thistechnique does not allow for the

estimation of the parameters of the polynomialcoefficients. When regression analysis is

used, these coefficients may be estimated (using SAS PROCREG, for example) and the

quality of fit may be assessed with the coefficient ofdetermination or the coefficient of

variation (Black, 1993).

The study of source, placement or timing of application offertilizers traditionally

included a selection of treatments, a positive control(often representing the industry

practice) and a non-treated control. In these studies,

treatment effect is determined using

mean separation tests (such as least significant difference– or one of its variants – Duncan

Multiple-Range test, Newman–Keuls’ test, Tukey’s test orScheffe’s test, for example)

using SAS PROC GLM. In these studies, the scientist expectsthat one or more of the

treatments will perform better than the positive control.In statistical terms, this means that

the scientist expects to reject the null hypothesis thatthe treatment means are equal. The

decision to reject the null hypothesis is made by takingthe type I risk (a) – typically set at

the 5% value (Gomez and Gomez, 1984).

In the BMP era, research focus has shifted from determiningoptimum rates for production

to an increase in input efficiency. These experiments seekto identify management

strategies that require lower input rates (especially waterand fertilizer), cost less and/or

result in less leaching while maintaining productivity(Jaber et al., 2005; Sato and Morgan,

2012; Simonne et al., 2014a; Ulén, 1999; Vázquez et al.,2006). This approach should

involve a different statistical approach that hassurprisingly received little attention in the

scientific literature. In the identification of moreefficient methods to produce crops, the

scientist often does not expect to reject the nullhypothesis (Gomez and Gomez, 1984).

Many research reports conclude that ‘based on these data,no significant differences were

found between these two production methods’ thereby leading

the reader to assume

that they are the same. Statistically, not being differentand being the same are two

different concepts. Statistical identity is declared undertype II risk (b) which is very seldom

calculated and reported.

4.2 Basics of power analysis

The power of an experiment is calculated as 1-b. Inputparameters in power calculation are

sample size (calculated as number of treatments multipliedby the number of replications),

type I error (a) and effect size (calculated as thedifference between group means that

needs to be detected divided by the variance; Cohen, 1988;SAS PROC POWER). In

practice, power may be increased by reducing the variance(which may be achieved by

increasing plot size) or increasing the number ofreplications. Power analysis of field data

from multiple fertilizer trials with tomato showed that apower of 0.80 might be achieved

with increasing the number of replications from 4 to 6 whenyield variance is �140 kg/HA

(Simonne et al., 2007b).

Often, today’s arguments between production agriculture andenvironmental protection

end in legal matters. The risk taken in accepting the nullhypothesis (in BMP research) is

as important as the one made in productivity improvement(in classic research). Scientific

journals and researchers should increase efforts to reportpower in today’s fertilizer and

irrigation projects when the null hypothesis fails to berejected. This will require first that a

consensus be reached on an acceptable value for power.

4.3 Adjusting fertilization practices to El Niño SouthernOscillation (ENSO) phases

While tomato growers may improve their irrigationmanagement, little they can do about

rainfall. Rainfall patterns in the Southeastern UnitedStates are climatically influenced by

El Niño Southern Oscillations (ENSO). ENSO is a natural,coupled atmospheric–oceanic

cycle that occurs in the tropical Pacific Oceanapproximately every 2–7 years. When sea

surface temperature (SST) in the eastern equatorial PacificOcean is greater by more than

2°C than the long-term average (or ‘normal temperature’),the phenomenon is called

El Niño. When the SST is lower than normal by more than2°C, the phenomenon is called

La Niña. The seasons when the SST is normal, are called‘neutral.’ In Florida, El Niño is

expected to bring 30%–40% more rainfall andcooler-than-normal temperatures during

winter and spring, whereas La Niña is expected to bringwarmer-and-drier-than-normal

winter and spring seasons. Since these are the main tomatoproduction seasons in Florida,

maybe irrigation and fertilization practices could beadjusted to the ENSO phases.

Long-term analysis of weather data from five stations inSouth Florida showed that winter

and spring average rainfall amounts during La Niña andneutral years were significantly

lower than during El Niño years (Fraisse et al., 2010).During El Niño years, at least one

leaching rainfall event of 2.5 cm or more in 1 day occurredat all four test stations and all

planting seasons and two of these events occurred in morethan 9 of 10 years except at

one weather station. During the fall growing season of ElNiño years, three to four 2.5 cm

or more in 1-day leaching rainfalls may be expected atleast 4 of 5 years at all five weather

stations. The probability of one or more leaching rainfallevent was less than 0.80. Based

on these results, N fertilizer supplemental applicationsallowed by the BMP programme of

35–140 kg/HA could be applied during the fall growingseason of all ENSO phases and

during all planting seasons of El Niño years (Fraisse etal., 2010; FDACS, 2015).

Using current fertilizer prices, one supplementalfertilizer application of 45 kg/HA of N

and 20 kg/HA of K costs approximately $120/HA. Assuming atomato median wholesale

price of $12 per 12-kg box, this additional cost may beoffset by a modest yield increase

of 10 boxes/HA (compared to a typical 2750, 12-kg box/HAmarketable yield). These

results suggest that ENSO phases could be used to predictsupplemental fertilizer needs

for tomato, but adjustments to local weather conditions maybe needed. This study did

not assess the environmental impact of these supplementalfertilizer applications; hence

this promising concept is currently embraced neither by theindustry nor by the regulators

(Ozores-Hampton et al., 2012).

In most of the scientific literature, irrigation andfertilization are studied and presented

separately (e.g. Bélanger et al., 2000; Goodlass et al.,1997; Parisi et al., 2006; Warner

et al., 2004; Wilcutts et al., 1998). Yet, the ultimateoutcome of production is determined

by the joint result of irrigation and fertilizationpractices (e.g. Baselga-Yrisarry et al., 1993;

Colla et al., 1999; Hegde and Srinivas, 1990; Morgan, 2015;Simonne et al., 2008, 2014a;

Zotarelli et al., 2009). The benefits of a soundfertilization plan may be lost because of

inadequate irrigation management. Hence, these twoproduction practices should always

be considered together and reported with the same amount ofdetails in the scientific

literature – which is unfortunately not the case today.

Fertilization practices (rate, placement and source) usedin commercial production

depend on the type of irrigation method used. The followingsections present the basics

of irrigation management, fertilization, and a summary ofrecommended practices for

commercial tomato production.

5 Irrigation management systems for tomato production

Water is a structural (80%–90% of total plant weight may bein water) and functional

component of tomato cells that is required for cellexpansion and growth, turgor pressure,

solute transport, and cooling of the plant (Farooq et al.,2009). Plants absorb water and

minerals from the soil solution mostly through their rootsystems (Salisburry and Ross,

1992). The cylindrical, filamentous form of the roots androot hairs contribute to the

absorption of ions and water (Steudle, 2001). Once absorbedby the root, water first

crosses the epidermis before moving towards the centre ofthe root crossing the cortex

and endodermis before arriving at the xylem. Water is thenmoved through the plants in

the open tubes of the xylem by the negative pressureproduced by the evaporation of

water from the leaves (Cramer et al., 2009). This processis commonly referred to as the

Cohesion-Tension mechanism (Steudle, 2002). Hence, tomatoplants need a continuous

supply of water throughout the season supplied from thesoil, rainfall or irrigation.

Tomatoes may be grown as a dry-land crop or may beirrigated with gravity, over-head

or drip irrigation systems (Locascio, 2005). In commercialproduction, irrigation is used as

a means to reduce the risk of crop failure if rainfall orsoil water reserves are insufficient.

5.1 Gravity irrigation systems

Also called ‘furrow irrigation’, these systems typicallyconsist in a water source (ground

water, pond water or river water), a pumping system, aconveyance system (open canals

and ditches) and a delivery system (small ditches placedevery two, three to six rows).

These systems are feasible when the fields are carefullylevelled and water infiltration rate

is low due to soil texture and/or characteristics (therebyallowing the surface conveyance of

water). These systems have long been used in the South WestUnited States and California

(Reddy and Clyma, 1981).

5.2 Seepage irrigation

Another gravity system called ‘seepage irrigation’,consists in the management of a water

table perched above a shallow impermeable layer. Thissystem is commonly used in

Florida. Delivery ditches are formed every three or sixtomato rows and the water moves

laterally and under the beds until the water front from twoadjacent ditches meet. Then,

the water moves upward and irrigates the plant bycapillarity (Sato and Morgan, 2012).

Water levels in the fields that are irrigated by gravityfluctuate slowly and it may take a

day or two to establish a uniform perched water table. Thisis advantageous when short

pumping failures occur. When rainfall events occur, excesswater needs to be drained out

of the fields, which takes time, may result in the removalof soluble nutrients, and may

result in temporary flooding of the fields.

Tomato plants are sensitive to the anoxic environmentcreated by flooding and have

shown adverse physiological responses after only 24 hoursof continuous flooding such

as reduced stomatal conductance and nutrient translocation(Bradford, 1983). Recent

work has shown that transgenic tomato plants may have

increased tolerance to flooding

(Grichko and Glick, 2001). Detailed responses of tomatoplants to flooding length and

timing as well as remediation strategies were reviewed byRao and Li (2003).

Gravity irrigation has the advantages that water issupplied constantly to the plants,

thereby avoiding water stress and foliage is not wetted.The main disadvantage of this

system is that a relatively large amount of water is neededto satisfy the transpiration

needs of the crops, the evaporation losses and theconveyance losses. Hence, water

needs to irrigate gravity-irrigated tomato plants typicallyrange between 100 and 150 cm

of water per crop (Dukes et al., 2012).

5.3 Overhead irrigation

Linear moves, centre pivots, travelling guns or solid setsare used mainly for processing

tomato production. When improperly designed or managed,some of these high-pressure

systems may mechanically damage tomato plants and fruits.Moreover, the repeated

wetting of tomato foliage may create a favourableenvironment for the development of

bacterial or fungal diseases (Rotem and Palti, 1969; Joneset al., 2014). Even if water usage

may be reduced to 50–75 cm of water per crop with thesesystems, their installation and

operation costs together with plant-health concerns make ita marginal choice for new

commercial operations.

5.4 Drip irrigation

Also known as ‘trickle irrigation’ or ‘micro irrigation’,drip irrigation is a low-pressure, low

volume method of irrigation that may only wet a portion ofthe field. Despite the level of

expertise and maintenance required, drip irrigation (withtubing placed on the soil surface

or buried) is the irrigation method of choice in mostcommercial operations worldwide.

Drip irrigation is an irrigation method that allows thedelivery of water directly to the root

zone through a network of valves, pipes, tubing andemitters (Runyan et al., 2007; Simonne

et al., 2015). Plasticulture is the combined use of dripirrigation, polyethylene mulch

and raised beds. The advantages of drip irrigation includelow-delivery pressure, high

uniformity, no wetting of tomato foliage and thepossibility to inject fertilizers, chemicals

and oxygen gas through the drip tape. Water needs fordrip-irrigated tomato fields range

between 20 and 40 cm of water per crop (Dukes et al.,2012). On the other hand, drip

irrigation has a relatively high cost of installation,involves a lot of specialized parts, and

requires high-quality water and maintenance. A maintenanceplan for a drip irrigation

system should include (a) filtration (using centrifugalsand separators or sand, disc or screen

filters), (b) chlorination with hypochlorous acid (HOCl) orsodium hypochlorite (NaOCl), (c)

flushing (both to reduce the risk of emitter clogging), (d)acidification (to increase the

efficacy of the chlorination), and (e) system observationand inspections (for leaks, tears, or

breakage) (Haman, 2014; Runyan et al., 2007).

6 Optimizing irrigation volumes and scheduling

6.1 Practical units for reporting irrigation amounts

For irrigation systems that wet the entire field (gravityor over-head systems), vertical

amounts of water well describe the water volume applied tothe field. For irrigation

systems that only wet a portion of the field (dripirrigation), a vertical amount of water

does not represent the actual water distribution. Verticalamounts of water were reported

in the previous section to generally describe the seasonalamount of water needed, as a

planning tool. Vertical amounts of water are also useful inthe calculation of surface-water

storage needs. Yet, for application purposes,drip-irrigation volumes should be reported

in L/100 m of row or L/HA. Noticeably, this is the unitused to describe drip-tape flow

rates (L/100 m or L/emitter) at known emitter spacings andoperating pressure (Poh et al.,

2011a,b).

6.2 Scheduling irrigation for tomato

Scheduling irrigation is determining when to startirrigation and how much to apply

(Allen et al., 1998). Combinations of the soil waterbalance and the chequebook method

consisting in daily recordings of soil water loss byevapotranspiration (withdrawals) and

drainage, and rainfalls and irrigation events (deposits),

allowed the calculation of soil

moisture status and the need for irrigation events (Smittleand Dickens, 1992). With

advancements in soil moisture sensing, wirelesscommunications, and the increased

need to conserve water, irrigation schedules for tomatotoday include (1) calculating a

target irrigation volume that represents cropevapotranspiration (ETc), (2) fine tuning the

schedule based on daily soil moisture measurements (soilwater tension or volumetric

water content), (3) determining the contribution ofrainfall to tomato plant water needs,

(4) developing a rule for splitting irrigation volume(highest volume for one event before

leaching is expected), and (5) keeping records of date andamount of rainfall and irrigation

events (Dukes et al., 2012).

6.3 Determining target irrigation volume

Early work seeking to determine tomato water needs reportedthat highest fruit yield

(about 110 000 kg/ha) from drip-irrigated tomatoes grown ona fine sand in Israel was

obtained when the daily average volumetric water content inthe soil root volume was near

5% and the N concentration in the soil solution was 140 �40 mg/L of N (Bar-Yosef, 1977).

The estimated water quantity used to produce 1 g dry matterwas about 250 � 40 g H 2 O/g

dry matter (Bar-Yosef, 1977).

Historical weather data may be used for estimating targetirrigation volumes especially

in staked tomato production (Dukes et al., 2012). Whentomatoes are kept erect through

the installation of strings weaved around the stakes, astring is added every two weeks.

Hence, the number of strings (1–4) has become a gauge ofplant growth in the field. Some

growers of staked tomato follow the ‘1,000gallon/day/string/acre’ rule of thumb as quick

estimate of target volume (9500 L/day/string/HA).

When real-time weather data are available, targetirrigation volume may be estimated

by crop evapotranspiration (ETc) based on crop stage ofgrowth. In practice, ETc may

be estimated through reference evapotranspiration (ETo,Allen et al., 1998) or Class A

Pan evaporation (Ep; Smittle and Dickens, 1992) using theformulae: ETc = Kc x ETo or

ETc = CF x Ep.

Large, precision weighing lysimeters are expensive butinvaluable tools for experimentally

measuring ETc and developing Kc or CF values (David et al.,2010). Because the concept

was first supported by FAO with bare-ground crops (Allen etal., 1998), much efforts have

focused on adjusting existing Kc values for tomato grownwith plasticulture in different

areas of the world. With tomato grown with plasticulture inthe Jordan Valley, Kc values for

early, mid and late season growth stage were estimated as0.65, 0.82 and 0.76, respectively

(Amayreh and Al-Abed, 2005), which represent 36% less thanthe FAO corresponding

value for bare-ground production.

In Tuscany, Italy, Kc values used were 0.35 from transplantto establishment, 0.55 until

early bloom, 0.90 during fruit set; 1.1 during fruitgrowth-veraison, and 0.95 from the

beginning of ripening until harvest (Tarantino and Onofri,1991; Marino et al., 2014). Using

the Bowen Ratio Energy Balance Method, average Kc valuesfor drip-irrigated processing

tomato grown in the San Joaquin Valley, California rangedfrom 0.19 at 10% canopy

coverage to 1.08 for canopy coverage exceeding 90% (Hansonand May, 2006a). A

California study that used a 6.1-m diameter lysimetersfound that Kc values of processing

tomato under sprinkler irrigation were 0.22 (initialstage), 1.25 (mid-season), and 0.6 (late

season; Pruitt et al., 1972). Allen et al. (1998) listedmid-season tomato Kc for various wind

speeds, ranging between 1.2 for wind speeds of 0–5 m/s and1.25 for speeds of 5–8 m/s.

A maximum average Kc value of 1.05 was found using alysimeter with drip lines buried

0.46 m deep in a clay loam soil in the San Joaquin Valley(Hartz, 1993). The mid-season Kc

value for processing tomato grown in the San JoaquinValley, developed in the 1970’ with

values of 1.25 and 1.05 for sprinkler and sub-surfaceirrigation, respectively, were updated

to 0.96–1.09 for either irrigation method (Hanson and May,2006b). In several cases, these

Kc estimates were further validated (Hartz, 1993;Baselga-Yrisarry et al., 1993).

These results and observation emphasize that specific Kc

values needed to be developed

for tomato grown with plasticulture and the conversionneeds to reflect the amount of soil

wetted by the drip irrigation which depends on soil typeand bed spacing. Based on

several previous studies, Stanghellini et al. (1990)commented that ratio of ETc to ETo

was not constant and concluded that, whenever knowledge ofa number of crop-specific

parameters is available, a ‘theoretical’ transpirationformula is likely to deliver better

estimates of crop water requirement than calculations basedon Kc. These experimental

and mathematical conclusions established the foundation foradjusting target water

application with real-time field-based data such as soilwater tension, soil volumetric water

content or canopy spectral radiance.

6.4 Fine tuning irrigation schedules based on dailyvolumetric or tensiometric soil moisture measurement

Several early studies determined the highest amount ofwater deficit tolerable to tomato

plants before fruit yields are reduced. Schedulingirrigation when the soil matric potential

reached 65 kPa resulted in highest tomato marketable yieldand a water use efficiency

that was greater than that recorded with irrigation at 85kPa but similar to that found at

25 and 45 kPa (Hedge and Srivinas, 1990). Fruit quality(measured as total soluble solids

and fruit firmness) increased with decreasing irrigationfrequency (Hedge and Srivinas,

1990). In Portugal, the water use efficiency of

drip-irrigated tomato was significantly lower

with irrigation at 10 kPa than with irrigation at 20, 40 or60 kPa (Do Rosário et al., 1996).

Other authors reported that tomatoes grown on a fine sandysoil using drip irrigation

and polyethylene mulch had higher yields when irrigationmaintained soil at 10 kPa as

compared to 15 or 20 kPa (Smajstrla and Locascio, 1996). Inaddition, the reduction in

yield with increasing water stress first occurred in theextra-large fruit category, which

would have the greatest economic impact on producers(Smajstrla and Locascio, 1996).

These apparently contradictory results suggest that even ifthe tomato sensitivity to water

stress is constant, the soil water tension threshold maydepend on the soil type because of

the shape of the soil water-release curves. Together, theseresults suggest that for practical

management of irrigation, the maximum tolerable soil watertension for tomato is 65, 25

and 10 kPa for heavy, medium-textured and sandy soils,respectively.

As water availability for crop production became anincreasing concern worldwide,

research efforts sought to identify stages during thegrowing period were irrigation rates

could be reduced. This method of irrigation consisting ofonly partially replenishing

soil moisture is called ‘deficit irrigation’. Withholdingdrip irrigation to ‘Mt. Spring’

tomato grown with plasticulture and drip irrigation for ashort period (between plant

establishment and first flower) increased fruit marketableyield by 8%–15%, fruit number

by 12%–14% while reducing amount of irrigation water by 20%compared to the fully

irrigated treatment (Ngouajio et al., 2006). This suggeststhat if soil moisture is adequate

at transplanting, subsequent withholding of irrigation for1–2 weeks after tomato

transplanting may increase yield while reducing the amountof irrigation water needed. It

is also possible that withholding irrigation when tomatoplants are small and root systems

are partially developed results in reduced risk of nutrientleaching. Water deficits imposed

to processing tomatoes grown in Viterbo, Italy, underreduced irrigation volumes to 50%

or 75% of ETc before fruit set reduced the number offlowers, leading to a decrease in fruit

number and marketable yield, and in an increase in solublesolids content (Colla et al.,

1999). However, water deficits improved the quality offruits by increasing soluble solid

content and acidity. Reducing irrigation by 25% beforefruit set and by as much as 50%

during the fruit development and ripening stages did notresult in a significant decrease

in soluble solid content (Colla et al., 1999). In SouthernItaly, extending the irrigation

interval and limiting irrigation volume for the second partof ‘Ability’ tomato production

appeared to be the best management strategy to optimize theyield and nutritional quality

of processing tomato (Favati et al., 2009).

In practice, soil moisture levels may be measured withtensiometers, time-domain

reflectometry probes or scanning probes. These tools havereplaced the traditional

gypsum blocks and granular matrix sensors (Muñoz-Carpena etal., 2015). While modern

devices are more durable, show a greater sensitivity tochanges in soil moisture, may be

accessed remotely and are often coupled with graphicsoftware, their placement in the

field remains the key to their usefulness: irrigation ofthe entire field will be based on the

moisture measurement near the probe. Beyond the generalstatement that ‘probes should

be placed in a representative area of the field’, littleinformation is available on probe

placement in the literature. Once a location that is‘representative of the field’ is identified,

probe placement needs further consideration in regard toposition on the raised bed

(centre, shoulder or somewhere in between), the drip tape(on the side of the tape or

on the side of the plants) and the tomato plants themselves(by a plant or between two

plants). On sandy soils, the wetted zone seldom extendsfurther than 15 cm from the drip

tape on each side (Simonne et al., 2014a). Hence,experience has shown that the spot the

most sensitive to changes in soils moisture on the bed ison the tomato plant side, 15 cm

from the drip tape and between plants.

6.5 Contribution of rainfall to crop water needs

The contribution of rainfall to crop water needs is

determined by the use of impermeable

polyethylene mulch, root system development and the size ofthe rainfall event (Ozores

Hampton, 2015). Polyethylene mulches act as a barrier torainwater and force most of

the water towards the row middles. Unexperienced tomatogrowers who are new to

plasticulture may find it counter intuitive to still haveto use drip irrigation after a large rain

especially with course-textured soils. In these soils,little lateral water movement from the

row middle occurs under the mulch.

In addition to their mechanical anchoring role, the mainphysiological functions of

root systems are to explore the heterogeneous soilenvironment and take up water and

nutrients. In addition, roots may form mutualisticassociations with key soil microorganisms

such as N-fixing bacteria and mycorrhizal fungi. Tomatoplants have a dense and shallow

root system. Using mini-rhizotrons installed between twoconsecutive plants and in

proximity of the plant row, showed that drip-irrigationtreatments significantly affected

root distribution of ‘Brigade’ and ‘H3044’ tomatoes alongthe soil profile (Machado et al.,

2003). A large concentration of roots at the depth of theirrigation tubes was found. For

both surface and subsurface drip irrigation and for bothcultivars, most of the root system

was concentrated in the top 40 cm of the soil profile,where root length density ranged

between 0.5 and 1.5 cm cm −3 (Machado et al., 2003). Using

the trench profile wall method

and drip irrigation treatments where the maximum allowablesoil water tension ranged

between 10 and 60 kPa, more than 88% of tomato roots werefound in the top 40 cm of

the soil and rapidly decreased with depth; most rootsoccurred in the emitter area, close

to the plant (Do Rosário et al., 1996). Zotarelli et al.(2009) confirmed that tomato root

distribution in a sandy soil mainly depends on thedevelopment stage, soil moisture and

nutrient availability. Tomato root concentration wasgreatest in the vicinity of the irrigation

and fertigation drip lines for all irrigation treatments.At the beginning of reproductive

phase nearly 75% of the total root length density wasconcentrated in the 0–15 cm soil

layer while 20% of the roots were found in the 15–30 cmlayer (Zotarelli et al., 2009).

Corresponding root length densities during the reproductivephase were 68% and 22%,

respectively.

Root system development may be affected by adverse growingconditions or stresses

such as soil compaction, oxygen availability, drought, soilpH and salinity (Hodge et al.,

2009).

6.6 Rule for splitting irrigation volume

When tomato plants are fully mature, the weather demand ishigh, and soils have a relative

low water-holding capacity, it is possible that daily ETcis greater than the amount of water

that can be stored in the root zone. In these cases,applying the entire ETc volume in one

irrigation cycle may result in water and soluble nutrientsmoving below the root zone.

When drip irrigation is used, the amount of water that canbe stored in the rootzone may

be estimated by multiplying the width of the actual wettedzone by the maximum rooting

depth by the length of bed (Farneselli et al., 2008). Whendrip irrigation is used on sandy

soils, lateral water movement seldom exceeds 15–20 cm oneach side of the drip tape,

resulting in a wetted width of only 30–40 cm (Simonne etal., 2014a). When the irrigation

volume exceeds the target values, irrigation should besplit into 2 or 3 applications each

day. Splitting will not only reduce nutrient leaching, butit will also increase tomato quality

by ensuring a more continuous water supply. Uneven watersupply may result in fruit

cracking.

6.7 Recording rainfall and irrigation events

Keeping records of rainfall patterns, irrigation schedules(timing and amount) and fertility

plans (source, rate, placement and timing) allow tomatogrowers to organize and record

cultural practices and are a required part of BMPimplementation (FDACS, 2015).

6.8 Real-time sensor-based irrigation scheduling

Recent irrigation studies aimed at reducing irrigationwater needs through tape placement

(surface or buried), increasing irrigation frequency (fromonce to multiple times daily), or

monitoring soil moisture throughout the soil profile.Subsurface drip irrigation and soil

moisture sensor-based systems consistently increased tomatoyields in Florida while

greatly improving irrigation water use efficiency andthereby reduced both irrigation water

use and potential N leaching (Zotarelli et al., 2009). A3-year field study showed that

sensor-based irrigation with the drip tape placedunderneath the plastic mulch required

15%–51% less irrigation water when compared tofixed-schedule treatments, while the

reductions in irrigation water use for 15-cm sub-surfacedrip irrigation were 7%–29%.

Annual tomato yields were 28, 56 and 79 t ha −1 for years1–3, respectively, and were

11%–80% higher for the surface and sub-surface tapeplacement than with the fixed

schedule (Zotarelli et al., 2009).

Low-volume, high-frequency irrigation schedules arepossible with a permanently

pressurized system and controlled by an irrigation timer.Using a timer set to irrigate a

maximum of five times per day with the irrigation timematching historical ETc values

reduced water use while not significantly affecting tomatoyields grown in a gravely soil

(Muñoz-Carpena et al., 2015). Using switching tensiometersset at the 15 kPa trigger

pressure resulted in a reduction in irrigation water of upto 73% compared to the typical

farm schedule (Muñoz-Carpena et al., 2015).

In Tuscany, soil water content was monitored at the 10, 20,30 and 50 cm depths using

a CropSense system (Marino et al., 2014). Rainfall duringthe crop cycle reached 162 mm

and irrigation water applied with a drip system totalled207 mm, distributed in 16 events.

Tomato yields ranged from 7.10–14.4 kg m −2 , with a wateruse efficiency ranging from

19.1–38.9 kg m −3 . The irrigation system allowed highyield levels and a low depth of

water applied, as compared to seasonal ETc estimated withHargraves’ formula and with

the literature data on irrigated tomato. This study alsoconcluded that several vegetation

indices were significantly correlated to tomato yield andwell identified, a posteriori, crop

area with low water use efficiency, hence showing thatspectroradiometry can be a valuable

tool to improve irrigated tomato field management (Marinoet al., 2014).

Advanced soil water flow simulation models may also reduceETc, provided that they

are calibrated and used with field data and that they aremathematically optimized with

Geographic Information System and remote sensing techniques(Scholberg et al., 1997;

Bastiaanssen et al., 2007). Obstacles to the wideutilization of these models include

(1) insufficient awareness of technical capabilities ofnumerical tools by irrigation

professionals; (2) limited access to computers; (3) absenceof required soil, weather

and/or crop data to operate these models; (4) naturalscepticism that computer-based

technology is useful for tackling practical irrigation anddrainage problems; (5) lack of

calibration protocol so that multiple and contrastingresults are often obtained; (6) poor

justification for model use and wrong model selection inhistoric studies; (7) models are

not specific enough for solving site-specific problems andquestions; (8) assumptions and

simplifications undertaken in the model are inadequate tosufficiently capture the intrinsic

structure of the system being modelled; and (9) highertrust in field measurements than

in model predictions (Bastiaanssen et al., 2007). Thelikelihood of adoption by a broader

model user community will increase if models become moreuser- and data-friendly and

heterogeneity-aware. Hence, these models are used today atthe watershed level rather

than at the field level.

7 Fertilization in tomato production: introduction andsoil sampling

Fertilization practices used in tomato production may bebased on two approaches – whether

fertilization is targeting the soil or tomato crop(Hochmuth and Hanlon, 2013). The ‘build-up

and maintenance’ approach seeks to increase plant-availablenutrients in the soil, especially

those with high cation exchange capacities (CECs) inregions where evapotranspiration

exceeds rainfall (so leaching risk is low) (Schepers etal., 1986). The Basic Cation Saturation

approach aims at adjusting the ratio of cations held in thesoil by the addition of fertilizers

to an ideal ratio of 70%, 20% and 10% for Ca, K and Mg,respectively. These approaches

are popular among grower who see build up and maintenanceas a method to reduce the

risk of nutrient shortage. On the other hand, theseapproaches ignore the risk of nutrient

loss through leaching, immobilization or atmospheric loss(Simonne and Morgant, 2013).

These approaches also assume that crop relative nutrientneeds match nutrient relative

base saturation. On the opposite end of the spectrum, thefield hydroponic approach

used in areas with coarse-texture sands ignores theinherently low soil-nutrient-holding

capacity; the soil serves as an inert physical medium;fertilization needs need to be

provided often and in small quantities of soluble nutrients.

The Crop Nutritional Requirement (CNR) method relies on thesoil’s ability to hold

nutrients and the amount of nutrients needed to produce atomato crop. The amount of

soil-available nutrients are determined by the results ofcalibrated soil-testing method;

fertilization is calculated as the difference between thecrop nutritional requirement and

the nutrients naturally supplied by the soil. All thesephilosophical approaches focus

on total nutrient rates needed to produce a tomato crop(Liu et al., 2015). Yet, nutrient

source, placement and time of application are as importantas rate in the development

of a fertility plan. This concept is represented by the 4Rs (right rate, right source, right

timing, right placement) promoted by the InternationalPlant Nutrition Institute (http://

www.nutrientstewardship.com/what-are-4rs) and manyuniversities worldwide.

Soil testing is defined as a chemical analysis that seeksto assess the plant-available

nutrient status, salinity and pH of a soil. Soil testmethods are soil-type specific, and are

used to predict crop response to fertilizer applications.Once a representative and well

composited soil sample is submitted to a diagnosticlaboratory, a soil extraction procedure

needs to be selected for releasing the soil-bound nutrientsinto solution. The selection is

based mainly on soil texture and pH. Universal extractionreagents, which are defined as a

single extractant for use on a range of soils for thedetermination of both major elements

and micronutrients, are widely used by soil testinglaboratories in the United States (Jones,

1990; Mylavarapu, 2009) and are briefly described below.

7.1 Mehlich-1 (M-1) extractant soil test

The Mehlich-1 (M-1) extractant soil test for phosphorous(P), also known as double acid or

North Carolina extractant, was developed for determiningbioavailable P in acid soils with

CEC of less than 10 cmol kg −1 (Mehlich, 1953; Nelson etal., 1953; Mylavarapu and Miller,

2013). The weak double acid mixture in the M-1 extractantis neutralized once the soil

pH is 7.0 or higher. So it should not be used with soilswith pH greater than 7.0.

7.2 The Mehlich-3 (M-3) extractant soil test

The Mehlich-3 (M-3) extractant may be used with all typesof acidic soils for extracting K,

Mg, Cu, Mn and Zn (Jones, 1990) and has been determined tobe useful as a P extractant

on a wide range of soil types (Hanlon and Johnson, 1984;Tran et al., 1990). The M-3

extraction procedure is being increasingly used in the USsouthern region (Hanlon and

Savoy, 2009) because of its improved extraction efficiencyand its broad applicability

(Mylavarapu et al., 2002). The M-3 extracting solutioncontains salt, dilute acid, fluoride

and ethylene diamine tetra-acetic acid (EDTA) buffered withacetic acid at pH 2.5.

Fluoride serves to solubilize Al cations that may bind withphosphates thereby increasing

the quantity of orthophosphate in solution; the acetic acidis beneficial for keeping the

solution buffered below pH 2.9 to prevent Ca fromprecipitating; NH 4 NO 3 serves to extract

K, Ca and Mg and EDTA is added to improve the extraction ofMn, Zn and Cu (Zhang et

al., 2013). The M-3 extractant is more reliable than M-1for estimating available P in soils

with pH >7.4 (Mallarino, 1997).

7.3 Olsen extractant soil test

The sodium bicarbonate soil test was developed to predictcrop response to P on

calcareous soils. It uses HCO 3 − , CO 3 2− and OH − tosolubilize P (Olsen et al., 1954). In

calcareous soils, Ca 2+ is precipitated as CaCO 3 , and Feand aluminium (Al) as iron (Fe) and

Al oxyhydroxides, thus enhancing P solubility. The originalOlsen method was modified

by Hunter (1979) to extract P, K, Ca, Mg, Zn, Cu, Fe andMn. The Olsen extractant was

reliable diagnostic tools for estimating available P insoils with pH equal to or greater than

7.4 (Mallarino, 1997).

7.4 Ammonium bicarbonate (AB-DTPA) extractant soil test

The AB-DTPA extraction reagent used on alkaline soils wasintroduced in 1977 (Soltanpour

and Swab, 1977). Alva (1993) observed that AB-DTPA methodwas not able to measure

soil Ca and Mg concentration due to the presence ofcarbonates in the solution. But

Hanlon et al. (1996) suggested Mg did not precipitate aseasily as Ca during the relatively

short 15-min extraction time, so AB-DTPA could successfullybe used for estimating P, K,

Mg, Fe, Mn, Zn and Cu availability in calcareous soils.

After extraction and analysis, soil test ratings (rangingfrom ‘very low’, ‘low’, ‘medium’,

‘high’ to ‘very high’) are associated with a probability ofcrop response to additions of the

nutrient (Hanlon and Savoy, 2009; Savoy, 2008). Whilewidely used and practical, these

rating scales create artificial differences when the soiltest value is near the boundaries of

adjacent ratings.

8 Nutrient sources for tomato production

8.1 Soluble fertilizer (SF)

Tomatoes are sensitive to high levels of ammonium (NH 4 + )

and ammonia (NH 3 ) (Barker and

Mills, 1980; Britto and Kronzucker, 2002; van der Eerden,1982). The preferred N source

for tomato production are nitrate (NO 3 − -N) and NH 4 +-N. With nutrient film technique

(NFT), highest tomato yield were observed with 100% NO 3 −-N solution and significantly

lower yields were measured for treatments containinggreater than 50% NH 4 + -N (Feigin

et al., 1980). Another NFT study reported that the dryweight of tomato plants produced

in solutions composed of 50:50: NO 3 − -N:NH 4 + -N wassignificantly lower than those of

plants grown with 100:0 and 90:10 NO 3 − -N:NH 4 + -Nratios (Errebhi and Wilcox, 1990). The

reduced biomass was associated with the incorporation of NH4 + into organic acids at the

expense of plant growth. Adsorbed NH 4 + decreases soilsolution concentration, thereby

alleviating the toxicity (Barker and Mills, 1980).Furthermore, nitrifying soil microorganisms

oxidize NH 4 + to NO 3 − , thereby lowering the risk oftoxicity.

When equal amounts of the NH 4 + and NO 3 − sources areapplied, plants absorb greater

quantities of NO 3 − compared with NH 4 + due tonitrification and preferential plant uptake

(Gweyi-Onyango et al., 2009). In a medium-textured soil,Guertal and Kemble (1998)

found no differences in tomato yield grown with potassiumnitrate (KNO 3 ), ammonium

nitrate (NH 4 NO 3 ) and urea. However, urea use should beavoided in tomato production

with fumigated soil. Without microbial populations totransform NH 4 + to NO 3 − , a buildup of

NH 4 + or volatilization may occur (Pietr and Slusarski,2003). Volatilization of NH 3 increases

with high soil pH and low CEC soils (Junejo et al., 2011).

8.2 Enhanced efficiency fertilizers (EEF)

These fertilizers reduce the risk of nutrient loss to theenvironment and subsequently

increase N-use efficiency (NUE; Slater, 2010). The threesubgroups of EEFs are (1) slow

release fertilizers (SRFs) contain N in a less-soluble,plant-unavailable form that usually

needs microbial degradation to become plant-available N;(2) stabilized fertilizers (SFs)

are applied concurrently with a chemical inhibitor to slowthe bacterial oxidation of

ammonium (NH 4 + ) to nitrate (NO 3 − ) or to slow theenzymatic transformation of urea to

NH 4 + (Trenkel, 2010); and (3) CRFs, are usually urea, NH4 NO 3 , KNO 3 or other SF coated

with a polymer (polyethylene and ethylene-vinyl-acetate orthermoplastics), resin (alkyd

type resins and polyurethane-like coatings), sulphur, or ahybrid of a polymer coating over

a sulphur-coated urea (Trenkel, 2010).

CRFs allow for a single fertilizer application. Nutrientrelease from CRF may be

affected by soil factors including temperature, moisture,osmotic potential, pH, microbial

populations and texture. Furthermore, factors intrinsic toCRF may also affect nutrient

release including nutrient composition, coating thickness,and CRF prill shape and

diameter (Du et al., 2006; Engelsjord et al., 1996; Huettand Gogel, 2000; Kochba et al.,

1990).

CRFs are more costly than soluble fertilizers which is anobstacle to wide use in tomato

production. However, mixtures of CRF and solublefertilizers have shown improved

performance compared to CRFs alone (Carson et al., 2014).

8.3 Cover crops

Cover crops such as hairy vetch (Vicia villosa Roth.),clover (Trifolium subterraneum L.),

crimson clover (T. incarnatum L.), rye (Secale cereale L.)or oat (Avena sativa L.) may be

incorporated in a conventional tomato production system asthey reduce weed pressure

(Campiglia et al., 2010) and provide 1 and 2 kg of organicN per 100 kg of dry weight

for grasses and legumes, respectively (Treadwell et al.,2008b). Using a combination of

tomato production systems in central Georgia on a Norfolksandy loam, tomato yield

was greater with chisel ploughing and moldboard ploughingthan with no-till in 1996 and

was greater with 90 and 180 than with 0 kg·ha −1 N in 1996and 1997. Minimum tillage

such as chisel ploughing, and 90 kg·ha −1 N can bettersustain tomato yield and reduce

potentials for soil erosion and N leaching than canconventional moldboard ploughing

tillage and 180 kg·ha −1 N, respectively (Yaffa et al.,2000).

Other benefits of using cover crops include recycling

unused nutrients from previous

vegetable crops, improving soil structure, increasing soilorganic matter and fertility,

retaining moisture, reducing the risk of nutrient leaching,decreasing soil density, suppressing

weeds, increasing population of beneficial insects,controlling erosion, managing plant

parasitic nematodes, increasing soil biological activity,enhancing metabolome quality and

increasing yields (Abdul-Baki et al., 1997a,b; McSorley,1998; Sainju and Singh, 1997;

Stivers-Young, 1998; Sullivan, 2003; Treadwell et al.,2008a, Neelam et al., 2008). Some

benefits may occur during the cover crop life cycle, whileother benefits may take effect

after the cover crop is incorporated into the ground(Treadwell et al., 2008b). Using the

mini-rhizotron method to measure tomato root density in aGreenville fine sandy loam soil,

Sainju et al. (2001) reported that the total number ofroots in the 1–32.5 cm depth was

greater with hairy vetch, crimson clover, and 90 kg N ha −1than with 0 kg N ha −1 . Number

of tomato roots per square centimetre of soil profile areaincreased from the 1 to 26.0-cm

depth and then decreased at greater depths.

Disadvantages of growing cover crops in a vegetableproduction system include

additional production cost, delayed vegetable planting,increased pest pressure,

immobilization of N fertilizer, and difficult to controlratoon vegetable crop (Treadwell

et al., 2008c). Also, the availability of N from the cover

crops may not coincide with tomato

crop N uptake requirements. Hence, in some cases, tomatoyield and quality may be

adversely affected by short-term shortages; or a short lagtime between the release of

the N from the cover crop and subsequent vegetable cropuptake can result in NO 3 -N

pollution by leaching (Weinert et al., 2002).

8.4 Compost

Through the action of bacteria and fungi, the compostingprocess converts raw organic

materials (such as raw manure, yard debris, turf clippingsor food scraps) with high C

content into a humus-stable form. In compost, more than 90%of the total N is in an

organic form and only 10% is in the inorganic forms of NO 3-N or NH 4 -N (Hartz et al., 2000).

Compost improves the performance of tomato crops directlythrough the release of

nutrients and indirectly through the control weeds(Ozores-Hampton et al., 2001a,b), the

suppression of plant diseases (Hoitink and Fachy, 1986;Hoitink et al., 2001), the increase

in soil organic matter, the decrease erosion risk (Tyler,2001), and the reduction of nutrient

leaching (Jaber et al., 2005; Yang et al., 2007;Ozores-Hampton et al., 1998, 2011; Ozores

Hampton and Peach, 2002).

Increased soil organic matter improves soil physicalproperties by decreasing bulk

density and increase available water holding capacity,chemical properties by increasing

CEC, pH, and macro- and micro-nutrient supplies(Ozores-Hampton et al., 2011; Sikora

and Szmidt, 2001) and biological properties by increasesoil microbial activity properties

(Ozores-Hampton et al., 2011). Therefore, application timemay not be as critical as

compared to raw animal manures.

Compost N mineralization rates or N availability vary basedon compost feedstocks,

soil characteristics and environmental conditions.Typically, N immobilization occurs

in composts with initial C:N ratio greater than 20:1 andmineralization occurred where

composts had a C:N ratio lower than 20:1. However, C:Nratio is not a reliable predictor

of N mineralization since it depends in the type of C(Prasad, 2009a; Rosen and Bierman,

2005; Wallace, 2006). Mineralization N rates guidelinesdevelop by Wallace (2006)

indicated the availability of N is 0%–20% or even negativein the first year and 0%–8%

in the following years. However, P and K do not react as Nwhen compost is added to

the soil. Phosphorus and K in compost are readily availableto plants. No differences

were found between compost and commercial P in studiesusing biosolids compost or

manure compost (Preusch et al., 2002; Sikora and Enkiri,2003). Hence a compost user

should be cautious when using compost as a N fertilizerbecause only a portion of the

N (5%–30%) will behave as a commercial fertilizer the firstyear, but all the P and K in the

compost will react as a commercial fertilizer(Ozores-Hampton, 2012). Therefore, compost

application on sensitive land to P addition should be donebased on crop P rather than N

crop requirements (Preusch et al., 2002; Sikora and Enkiri,2003). Proposed P availability

from various compost made from different feedstock relativeto superphosphate are

available for spent mushroom compost (100%), animal manures(90%), source-separated

food waste (75%) and yard waste (60%) (Prasad, 2009b).However, generally for compost

or raw animal manures, 70%–80% of the P and 80%–90% of theK are available from

manure during the first year after application (Rosen andBierman, 2005).

8.5 Raw animal manures

Raw manures supply organic matter as well as plant macro-and micro-nutrients. Manure

applications may improve soil structure or tilth, increasesthe water-holding capacity,

improves drainage, provides a source of slow-releasenutrients, reduces wind and water

erosion, and promotes growth of earthworms and otherbeneficial soil organisms (Rosen

and Bierman, 2005). However, in areas of intense animalproduction, over-fertilization with

animal manure often occurs (Paik et al., 1996). The resultis often manifested by nutrients

entering water bodies.

In order to obtain maximum economic value of plantnutrients in animal manure and to

protect water supplies from excessive nutrient runoff or

leaching, animal manure should

be applied to match the most environmentally limitingnutrient needs of a crop. In some

states, application of higher manure rates than the mostlimiting environmentally sensitive

nutrient that are required by the vegetable crop [N orphosphorous (P)] is illegal. The

remaining nutrient amount, if any, must be supplied throughthe use of soluble fertilizer

(Eghball and Gilley, 1999).

The nutrient content in manures varies with animal type,bedding, storage, and

processing. Nutrient analysis of manure may be required bylaw in some cases, but analysis is

always recommended and should include total N, NH 4 -N, P 2O 5 and K 2 O. Usually 25%–50%

of the organic N in fresh manure will be available duringthe first year (Rosen and Bierman,

2005). If the manure contains bedding or is composted, theorganic N percentage will be

lower. Raw animal manure contains more NH 4 -N content thancompost, which increases

the risk of volatilization to ammonia (NH 3 ) gas.Therefore, raw animal manure should be

field incorporated within 12 h of application to reduce NH3 -N losses (Rosen and Bierman,

2005).

9 Optimizing nitrogen (N) rates

9.1 Field and mathematical determination of optimal N rates

The determination of optimal fertilizer rates for tomatoproduction is in theory very

simple (Black, 1992; Liu et al., 2015). First, a field with

a documented ‘low’ level of the

nutrient of study is selected and a fertility programmethat supplies adequate levels of

all the other nutrients is developed. These steps ensurethat the experimental treatments

used (rates of the element of study) are all limitingproduction, thereby allowing the

trial to represent the true response of tomato to rates ofthe selected nutrient. Then, a

range of rates is selected to cover the ‘low’, ‘reasonable’and ‘excessive’ rates with the

hope that the optimal rates will be within that range.Typically, treatments are selected

in regular increments (30 or 40 or 50 kg/HA increments, forexample). The next step is

to develop an experimental plan that allows for thereplication and randomization of

the treatments and growth of the crop in conditions asclose as possible to commercial

conditions. Tomato fruits are harvested following acommercial schedule (typically three

times for determinant varieties, once for processingvarieties and multiple times for

indeterminate varieties). Data are collected with gradedistribution at each harvest for

each experimental unit. The statistical analyses of ratedata should be performed using

regression analysis (and not means comparison tests). Ratesare on the x-axis and yield

on the y-axis. The researcher is then confronted to aseries of major decisions (that in

practice are addressed before the trial is conducted).

First, what yield data (total, marketable,

harvest-by-harvest, partial cumulative) should

be used on the y-axis? While this point seems fairlystraightforward, the experimenter

notices decreased group variance when partial cumulative orseasonal yields are used.

In some instances, relative yields (the highest treatmentyield is given a value of 100,

and all the other groups are expressed relatively to thisgroup means) have been

suggested for corn (Zea mays L.) (Black, 1992) and usedwith tomato (Hochmuth and

Hanlon, 2014).

Second, what rate value best represent treatments? Incommercial production, fertilizers

are seldom applied all-at-once in the field (the mainexceptions is when seepage irrigation

is used). A fertility programme typically consists of apre-plant application followed by one

or two side-dress applications (processing tomato) or dailyor weekly injections of fertilizer

(when drip irrigation is used). Using grape tomato as anexample, selecting the seasonal

rate to describe the first harvest yield response tofertilizer rate would count fertilizer

that has not yet been injected. In this case, it ispreferable to use the amount of nutrient

applied until that harvest [pre-plant plus injections(Simonne et al., 2008)].

The third question an experimenter faces is what functionbest describes the relation

between yield and rate? The mathematical options are many:polynomial (linear or

quadratic) or non-polynomial (linear plateau, quadratic

plateau, logistic function).

Comparisons of different models have been made with sugarbeet (Beta vulgaris L.) and

potato (Solanum tuberosum L.) (Neeteson and Wadman, 1987),lettuce (Lactuca sativa L.)

(Willcutts et al., 1998), potato (Belanger et al., 2000) ormany vegetables (Goodlass et al.,

1997) based on the proportion of the variability explainedby the model (R 2 , adjusted R 2 )

or the residual sum of squares (SSE). Despite thesein-depth analyses, no single model

has emerged as the ‘best’. However, these methods produce amore or less ‘liberal’

(numerically large) optimal yield, the quadratic polynomialbeing the most liberal, and the

linear plateau being the most conservative. Becauseresearchers have selected different

answers to these questions, virtually all options may befound in the literature. This may

explain why, surprisingly, no meta-analyses of tomatoresponse to fertilizer rates are

currently available.

9.2 Tomato response to N fertilizers

Much work has been done and summarized on processing(Dumas, 1990) and fresh

market (Hochmuth, 2003; Hochmuth and Hanlon, 2014)tomatoes. Fertilization studies

conducted in the last 60 years in Florida with tomato grownwith polyethylene mulch

showed how much varieties, growth-habit types, plantspacing, planting dates and

length of growing season (from 22 to 30 weeks for thedeterminate round types and the

indeterminate grape-type varieties, respectively), andirrigation management practices

have changed (Hochmuth and Hanlon, 2014). The analysis ofrate studies may be done

on original yield data (Stark et al., 1983; Ozores-Hamptonet al., 2012; Warner et al.,

2004) or on relative yield data (Hochmuth and Hanlon, 2014)as described by Black

(1992).

Using N partitioning and balances under a wide range of Nfertilization rates, Stark et al.

(1983) found that total N uptake was linearly related to Napplication and became less

than the amount applied at N rates greater than 300 kg ha−1 . They further concluded that

adequate N can be applied to tomatoes using high-frequencyN fertilization without large

denitrification N losses.

In replicated on-farm trials testing with seepage-irrigatedtomato and using N rates

ranging from 22–470 kg·ha −1 , extra-large and totalmarketable fruits yields showed a

quadratic plateau response to N rates with maximum yieldsat two harvests (97% of the

yields) grown with 172 and 298 kg N/ha in 2007 and 2008,respectively (Ozores-Hampton

et al., 2012). Total fruit yield of four processing tomatovarieties grown over four seasons in

south-western Ontario, Canada, increased linearly as N ratewas increased between 0 and

250 kg/ha except during the dry year. In years whensufficient soil water was available, N

rates of at least 200 kg ha −1 were required to producethe maximum marketable yield for

all varieties. In the dryer years, the response tofertilizer N rate was variety dependent, and

the application of 150–200 kg N ha −1 was sufficient tomaximize marketable yield (Warner

et al., 2004). Nitrogen fertilizer above the rate requiredfor maximum marketable yield

increased green fruit yield at harvest. Nitrogen rate didnot affect the soluble solids (SS)

content, firmness, size or colour of marketable fruit(Warner et al., 2004).

Increasing N fertilization from 0–250 kg N ha −1 increasedtotal yield of processing tomato

grown in 2002–2003 in the Sele Valley, Italy, but notmarketable yield, because of a strong

increase of unmarketable yield. The highest rate suppliedresulted in less concentrated

ripeness, more phytosanitary problems and an increase ofviral damage incidence on fruits

(Parisi et al., 2006). High N supply worsened someimportant processing characteristics

such as pH, soluble solids, glucose and fructose content aswell as the reducing sugar/total

solids ratio (Parisi et al., 2006).

The variability in optimal N rate for tomato productionreported by these studies

emphasizes the need to conduct these rate studies at thelocal level. Like for Kc values for

irrigation, a single N rate is not practical. Moreover,researchers may determine if a season

was ‘wet or dry’ or ‘hot or cold’ once the growing seasonis over, whereas tomato growers

need to make purchase and application decisions before andduring the season without

the knowledge of what the temperature and rainfallconditions will be.

10 Fertilizer recommendations, nutrient uptake andleaching

Few recommendations are accessible on the web outside theUnited States where fertilizer

recommendations for tomato are typically developed, testedand published by Land-Grant

Universities. Recommendations for fresh-market tomato grownin California (Le Strange

et al., 2000), the Southeastern states (Kemble, 2014) andFlorida (Freeman et al., 2016)

include rates, placement, timing and source information.Evidence exists that specific

recommendations are needed for grape (Simonne et al., 2008)and grafted (Djidonou et al.,

2013) tomatoes. Fertilization plans for tomato consist of(1) soil testing and understanding

the recommendation, (2) monitoring tomato plant nutritionalstatus during the crop cycle

with leaf analysis or petiole-sap testing, (3) trappingresidual nutrients with a cover crop,

and (4) keeping records (Morgan, 2015). Interpretative datafor leaf nutrient content based

on crop physiological stage are available for round(Hochmuth et al., 2015; Piggott, 1986)

and processing (Bryson and Mills, 2015) tomatoes. DRIS(Diagnosis and Recommendation

Integrated System) nutrient indices are also available forprocessing tomatoes (Hartz et

al., 1998). Petiole-sap threshold data are available forround (Freeman et al., 2016; Taber,

2001) and grape (Simonne et al., 2008) tomatoes for NO 3 -Nand K diagnoses.

10.1 Nutrient uptake by tomato plants

Plant roots may access essential nutrients from the soil bythree mechanisms: root

interception, mass flow, and diffusion (Bryson and Mills,2015; Epstein and Bloom,

2005). Root interception occurs as root tips grow orelongate into new areas of the

soil and get in close proximity of or in contact withnutrients. The amount of nutrients

intercepted this way is overall minor. Diffusion is themovement of nutrient molecules

or ions along a concentration gradient from a zone ofhigher concentration to a zone

of lower concentration. Mass flow is the movement ofdissolved nutrients to the root

surface through flowing soil water. The continuoustranspiration stream causes the

continuous movement of soil water solution to the rootsurface (Cramer et al., 2009).

Each essential element is primarily absorbed according toone of these three methods

(Chapin et al., 2011): mass flow is the dominant means ofabsorption for nitrogen

(NO 3 − ), calcium (Ca ++ ) and magnesium (Mg ++ ), sulphur(SO 4 −− ), iron (Fe ++ ), manganese

(Mn ++ ), boron [B(OH) 4 − ], copper (Cu ++ ), andmolybdenum (MoO 4 −− ); diffusion is the

primary means of supply for phosphorus (H 3 PO 4 − ), andpotassium (K + ); root interception

is a secondary method for Ca ++ and Mg ++ absorption;and, diffusion is the secondary

mechanism for N uptake.

10.2 Nutrient loss through leaching

Soluble nutrients that are not taken up by plants may beexposed to leaching. The

experimental determination of nutrient loads (usingnutrient flow models, nutrient balances

or drainage lysimeters), nutrient load estimates (andassociated precision), and field factors

that affect them and strategies for reducing the risk ofnutrient leaching (including the use

of chemical inhibitors, grafting, and irrigation schedulingwere recently reviewed (Simonne

et al., 2017). The concept is simple; its measurement isnot.

The risk of nutrient leaching caused by the mismanagementof irrigation in tomato

production in the Ebro Valley, Spain, was highest early inthe season (Vázquez et al., 2006).

Actual estimates for processing (Vázquez et al., 2006) andfresh-market (Lecompte et al.,

2008; Yaffa et al., 2000) tomato ranged from a few kg toseveral hundreds of kg. This

wide range was attributed to differences in methodology(soil sampling, soil solution, or

actual drainage), calculations needed to convert measuredleaching into field surfaces,

or N fraction measured (total N, mineral N, or NO 3 -N).These experimental challenges

together with the variability in actual nutrient leaching(based on in-field soil variability

and rainfall amounts) highlight some of the difficulty inthe experimental determination of

nutrient load at the field level.

11 Implications of water and fertilizer use for foodsafety

Tomatoes that are commonly consumed raw are subjected tothe produce safety rules

to reduce the risk of consumer foodborne illness in theUnited States (http://www.fda.

gov/Food/GuidanceRegulation/FSMA/ucm334114.htm). Accordingto the produce safety

rules in the Food Safety Modernization Act (US Congress,2011), tomato producers

must comply with key requirements on water quality, organicsoil amendments, wild and

domestic animals, and worker health and hygiene (FDA,2016). Currently the FDA, USDA,

public and private entities are partnering to educate andassist the produce industry,

including tomato producers to understand and implement theproduce safety programme

(http://producesafetyalliance.cornell.edu/).

Trace-back investigations of the multiple outbreaks in theUnited States from 1990 to 2010

suggested that the contamination had occurred on farms, atpacking houses or at fresh-cut

processing facilities showing that contamination may occurat any point from farm to table

(Bennett et al., 2015). Because field-grown tomatoes areconstantly exposed to potential

sources of contaminations, tomatoes are washed in a 200mg/L free-chlorine water before

grading, sorting and packing (Sargent et al., 2014). Yet,Salmonellae that infected the

tomato flowers or the stems in the field can survive until

the fruits ripe (Guo et al., 2001).

More recently, Zheng et al. (2013) confirmed that tomatoplants, especially within three

days of transplanting can be susceptible to increasedinternalization of Salmonella and

thereafter to the colonization and internalization ofSalmonella enterica in tomato plants.

This internalization may result from improper composing ofmanure which may contain

bacteria that are pathogenic to humans.

In order to reduce foodborne illness risk during tomatoproduction, the FDA does not

contradict the USDA’s National Organic Program(https://www.ams.usda.gov/about-ams/

programs-offices/national-organic-program) which requires120-day interval between

application of raw manure on crops which harvested partsare in direct contact with soil

and harvest. This interval is only 90 days for crops whichharvested parts are not in contact

with the soil. While detailed requirements are stillforthcoming, the key requirements can

found from the FDA factsheet for the FDA Produce SafetyFinal rules (FDA, 2016). For

instance, the composting process temperature must remainbetween 55 and 77°C (131

and 170(F) for 3 days in an in-vessel or static aeratedpile or for 15 days in windrows

(which must be turned at least 5 times during this period)to reduce human and plant

pathogen, nematodes, and weeds to acceptable levels(https://www.epa.gov/agriculture/

agriculture-nutrient-management-and-fertilizer).

Despite diligent industry efforts, fresh-market tomatoeshave been implicated in several

Salmonella and other foodborne diseases outbreaks over theyears (Bennett et al., 2015).

Tomato recalls for food-safety purposes have devastatingeconomic consequences;

shortly after a food-safety-based recall, consumerconfidence in the produce is shaken,

consumption and demand drop, thereby creating anoversupply; then, prices plummet.

Because of the magnitude of the foodborne illness burdensdue to fresh produce,

and as a part of US President Clinton’s 1997 food-safetyinitiative, the Food and Drug

Administration (FDA), the Environmental Protection Agency(EPA) and the Department of

Agriculture (USDA) released in 1998 the first food-safetyguidelines for the produce industry

called Guide to Minimize Microbial Food Safety Hazards forFresh Fruits and Vegetables

also known as the ‘Good Agricultural Practices and GoodHandling Practices’ (GAP/GHP)

(CDC, 2012; USDA-AMS, 2016). The GAP/GHP provide guidelinesfor fresh produce

industry to voluntarily implement the food-safety programmeto prevent the foodborne

diseases. The GAP/GHP guidelines cover water uses(agricultural and processing water),

manure and municipal biosolids usages, worker health andhygiene, sanitary facility, field

sanitation, packaging facility sanitation, transportationand trace back. In addition, to

further protect the produce industry, produce specific

programmes such as tomato GAP

(T-GAP) were developed and implemented in Florida insubsequent years (FDACS, 2016).

More recently, the US Food Safety Modernization Act (FSMA)of 2011 further focuses on

produce safety (US Congress, 2011).

12 Teaching water and nutrient management to tomatoproducers

12.1 Role of US land-grant universities in water andnutrient management education

In the United States, the role of public universities insupporting agriculture was defined

in the Morrill (US Congress, 1862, 1890), Hatch (USCongress, 1887), and Smith-Lever

(US Congress, 1914) Acts. These acts created the ‘US LandGrant System’ of Agricultural

Experiment Stations, Colleges of Agriculture, and ExtensionServices. Under these

legislations, the public land-grant universities were (andare still today) authorized to (1)

conduct the research needed to update science-basedproduction information (including

fertilization and irrigation for tomato production), (2)develop production recommendations,

and (3) facilitate the knowledge transfer to tomato growerseither directly through the

specialists and Extension agents of State’s CooperativeExtension Service, indirectly

through the training of Certified Crop Advisers(https://www.certifiedcropadviser.org) or

virtually through eXtension(http://articles.extension.org/category/vegetables).

12.2 Steps in teaching water and nutrient management to

producers

The goal of grower education through Extension interventionis to update the practices

used by growers in the areas of irrigation, nutrition,workers’ protection, and food safety to

the latest available information. Using the foundation ofthe logic model (Israel, 2013), the

adoption of change in fertilization and irrigationpractices used by tomato growers may

involve (a) increasing awareness that current practicesused may need to be improved,

(b) increasing tomato growers knowledge on the principlesand state-of-the-art, science

based recommendations for water and nutrient management,and (c) facilitating the

adoption of change through education, demonstration andfollow up. This is as much as

psychological process as it is a technical and financialone. Change is a slow process.

12.3 Improving water and nutrient management by tomatogrowers: the example of North Florida

Spanning over a 20-year period, this example illustrateshow UF/IFAS research and

extension personnel have facilitated the change infertilization and irrigation practices by

tomato growers in the Suwannee Valley basin of NorthFlorida (Simonne et al., 2014a).

Historically, vegetable growers have used irrigation andfertilizer amounts in excess of

recommended rates because they believed they gained aneconomic benefit from doing

so and they did not understand that excessive irrigationleaches mobile nutrients below

the root zone. The first step was to do the appliedresearch. Using Brilliant Blue FCF dye

as a tracer, a series of replicated trials was establishedat research and education centres

to visualize and quantify the movement of irrigation waterin mulched beds. These results

showing that (a) the waterfront was moving at a rate of0.012 and 0.017 cm/L/100 m and

(b) the maximum wetted width was approximately 20 cm oneach side of the drip tape,

were used to fine-tune the irrigation and fertilizationrecommendations of the University of

Florida (Freeman et al., 2016).

The second step was to increase growers’ awareness andknowledge by using

combinations of traditional classroom-style instruction,peer-reviewed publications and

hands-on experiential learning through hands-on activities,demonstrations and farm

visits. The goal was to increase the adoption of BMPs(FDACS, 2015).

Designed and offered by the Florida Cooperative ExtensionService, the Florida Drip

Irrigation School was developed as a 1–2-day educationprogramme that include lecture

style presentations, in-field and hands-on demonstrations,and video (http://vfd.ifas.ufl.

edu/water-nutrient-management.shtml). How-to and practicalinformation is presented on

irrigation system design, components, and installation;irrigation scheduling; calculations

for fertilizer applications; delivery of fertilizers andchemicals through the drip irrigation

system; movement of water, fertilizers, and chemicals inraised beds; drip irrigation system

maintenance; monitoring plant nutrient levels and soilmoisture levels during the growing

season using portable tools such as sap-meters and TDRs.

Dye tests were also conducted on commercial fields wheregrowers could see how their

own management practices were affecting water movement inmulched beds and under

what circumstances nutrients were moved below the root zone(Simonne et al., 2014b).

The third step was to show growers that ‘less is better’when it comes to water and

fertilizer application. Extension personnel also helpedvegetable growers in better

managing irrigation and fertilization by using portabletime-domain reflectometry probes

(TDR) and sap testing to estimate crop NO 3 -N and Knutritional status (Simonne et al.,

2009).

The last step was to observe and document how growers werechanging their practices.

Qualitative and quantitative data collection methods suchas surveys, pre-training/post

training tests, follow-up phone calls, personal interviewsand farm visits documented the

impacts of these educational activities. For example: •Three hundred and ninety-three small farmers attendeddifferent drip irrigation and nutrient managementextension education programmes over the last six years. Theaverage knowledge gain was 89%. • As a result of the dripirrigation management programmes 91% (132 attendees) ofthe farmers intended to adopt drip irrigation and nutrientBMPs on their farms. • Thirty-five vegetable growersadjusted their irrigation practices based on on-site soilmoisture readings. • Thirty-five vegetable growers are

verified to have adopted additional irrigation andnutrient BMPs including irrigation sensors, petiole-saptesting, improved irrigation management and refinedfertilizer rates. • Producer savings from reduced inputs,fertilizer and fuel, were approximately $200 per hectare,nearly $450 000 total for cooperative producers.

Overall, growers participating in the programme havereduced their irrigation and

N and K fertilization early in the season by 50% and 25%,respectively (Simonne et al.,

2014a). The availability of cost-share programmes to offsetthe cost of purchase of the

measuring instruments is poised to help make these culturalpractice changes permanent

(FDACS, 2015).


Global projections of world population growth suggest thatthe demand for food – including

fruits and vegetables and thereby all types of tomato – isgoing to increase. Areas attractive

for humans to live in are those with mild climates,abundant water, and plenty of sunshine.

These are also the areas favourable for tomato production.Consumers today also expect

a reduced carbon food print and a clean environment. Hence,the competition for land

and water between human consumption and food productionwill increase. Production

areas may shift closer to population centres. Ironically,as this competition develops,

production agriculture is likely to become moreintensified. Greenhouse production and

urban agriculture will have a central role. ‘Horizontalproduction’ may be replaced partially

with ‘vertical production’ as a means to preserve space.


For basic information on tomato, water, nutrientmanagement, and agricultural statistics,

consult ‘Tomato and other Solanaceous fruits’ (Simonne etal., 2011 in this chapter’s

reference section), ‘Compendium of Tomato Diseases andPests’ (Jones et al., 2014), ‘Crop

evapotranspiration: Guidelines for computing crop waterrequirements. FAO Irrigation

and drainage paper 56’ (Allen et al., 1998),‘Drip-irrigation systems for small conventional

vegetable farms and organic vegetable farms’ (Simonne etal., 2015), ‘Mineral nutrition of

higher plants’ (by H. Marshner, Academic Press, 2011),‘Nutrient management of vegetable

and row crop handbook’ (Morgan, 2015), Managing fertilizersto enhance soil health

(Singh and Ryan, 2015), ‘Plant analysis handbook IV’(Bryson and Mills, 2015), ‘Slow-and

controlled-release and stabilized fertilizers: An optionfor enhancing nutrient use efficiency

In agriculture’ (Trenkel, 2010) and ‘Statistical proceduresfor agricultural research’ (Gomez

and Gomez, 1984).

Scientific updates on tomato irrigation and fertilizationmay be found from the websites

and the scientific journals of the World Vegetable Center(http://www.avrdc.org/), the

International Plant Nutrition Institute(https://www.ipni.net/), the International Society

for Horticultural Science (http://www.ishs.org/), theAmerican Society for Horticultural

Science (http://ashs.org/), the International Society ofOrganic Agriculture Research

(http://www.isofar.org/), the International Association forFood Protection (http://www.

foodprotection.org/), or the US Composting Council(http://www.compostingcouncil.

org). Further advancement of tomato production will requirethe scientific connection

between current production practices and functionalgenomics through the use

of specific tomato genes held in the tomato germplasmcollection (https://www.

ars.usda.gov/northeast-area/geneva-ny/plant-genetic-resources-research/docs/

tomato-collection/). Analytical methods used for soiltesting, plant tissue and sap

analyses, and tomato nutritional content are scientificallytested, adopted and modified

by the Association of Official Analytical ChemistsInternational (http://www.aoac.org/).

Trade and consumer information on tomato production,handling and processing

may be found from the World Tomato Society(https://www.worldtomatosociety.com/

join/), the World Processing Tomato Council(http://www.wptc.to/), the International

Irrigation Society (https://www.irrigation.org/), theNational Greenhouse Manufacturers

Association (https://www.ngma.com/), or the United FreshProduce Association (http://

www.unitedfresh.org/).

Laws, standards and regulatory updates applying to theproduction, grading, food

safety and food composition of tomato may be different forevery country. In the United

States, these laws are established by the US Congress andimplemented and enforced at

the federal level mostly by the US Department ofAgriculture (USDA), the FDA, and the

EPA. Federal regulations are implemented the state level byappropriate state agencies.

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Zotarelli, L., M. D. Dukes, J. M. Scholberg, T. Hanselman,K. L. Femminella and R. Muñoz-Carpena. 2008a. Nitrogen andwater use efficiency of zucchini squash for a plastic mulchbed system on a sandy soil. Scientia Hort. 116(1):8–16.

Zotarelli, L., J. M. Scholberg, M. D. Dukes and R.Muñoz-Carpena. 2008b. Fertilizer residence time affectsnitrogen uptake efficiency and growth of sweet corn. J.Environ. Qual. 37:1271–8.

Zotarelli, L., J. M. Scholberg, M. D. Dukes, R.Muñoz-Carpena and J. Icerman. 2009. Tomato yield, biomassaccumulation, root distribution and irrigation water useefficiency on a sandy soil, as affected by nitrogen rateand irrigation scheduling. Agric. Water Manag. 96(1):23–4.

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5 Chapter 5 Understanding and improvingwater-use efficiency and droughtresistance in tomato

1 Introduction

Plant physiology is a broad sub-field of botany concernedwith how plants function.

It is customary to divide plant physiology in disciplinesdealing specifically with water

relations, photosynthesis and respiration, biotic andabiotic stress and mineral nutrition.

As sessile organisms, plants need to adapt theirfunctioning to contingent environmental

conditions, which can vary broadly over time. Thus, plantdevelopment and physiology

are intimately linked throughout a plant’s life cycle. Thetomato (Solanum lycopersicum L.)

is both a well-established genetic model for plant biologyand a horticultural cash crop

with an increasing importance for human nutrition. Researchin tomato physiology has

a rich history which includes many conceptualbreakthroughs. On the applied side,

production of cultivated tomatoes is divided broadly intotwo categories: greenhouse

grown tomato for fresh consumption and field-grownprocessing tomato for industrial

use. The latter attracts the largest share of the researchand breeding effort. Tomato is

mainly cultivated under irrigated conditions, so water useis of considerable relevance

for healthy plant growth and adequate yield. The comingyears will see a growing

competition for the use of freshwater between agricultureand industrial/residential

consumption. It is therefore desirable to increase ourunderstanding of water relations in

tomato. Our goal in this chapter is to review recentadvances in tomato physiology, with

particular emphasis on the promising convergence betweendevelopmental physiology

and water relations. We also endeavour to integrate recentfindings with selected earlier

studies.

2 Tomato as a genetic model in plant biology

The use of tomato as a model for plant biology goes back tothe 1940s, when Went,

Thimann and Skoog carried out their pioneering work on thehormone auxin using tomato

(Kramer and Went, 1949; Went, 1944a,b; Thimann et al.,1942; Skoog, 1940). In the late

1950s, Hans Stubbe established the first collections ofmutant germplasm in tomato,

produced by various chemical and physical treatments(Stubbe, 1957, 1958, 1959). This

was an important step towards the creation of a largerepository of allelic variation to

study the effect of particular mutations in the growth andfunction of the tomato plant. It

was, however, the seminal work of Charles Rickcharacterizing natural genetic variation in

the tomato clade in the 1960s and 1970s and of MarteenKoornneef isolating mutants in

the 1990s which established the tomato as a genetic modelfor plant development and

physiology (Kendrick et al., 1997; Koornneef et al., 1990;Peters et al., 1989; Rick and

Yoder, 1988).

Tomato is part of the Solanaceae family, which includes abroad number of species

of economic importance like chili pepper (Capsicum spp.),potato (Solanum tuberosum),

tobacco (Nicotiana tabacum), eggplant (Solanum melongena)and petunia (Petunia spp),

among others, making it one of the most extendedly studiedplant families in the world.

Tomato is one of the most important horticultural crops, asit represents a major dietary

source of vitamins and antioxidant compounds that are keyto human nutrition (Siddiqui

et al., 2015; Raiala et al., 2014). Furthermore, tomato hasbeen gaining popularity as

a plant model in both basic and applied research as it wasone of the first eudicots to

have its complete nuclear genome sequenced (The TomatoGenome Consortium, 2012).

Progress in genome sequencing techniques in recent yearshas allowed the completion

of the nuclear genomes of other solanaceous species throughthe effort of various joint

international consortia (Fernandez-Pozo et al., 2015;Mueller et al., 2005), among them

potato (Solanum tuberosum) (The Potato Genome Consortium,2011), tobacco (Nicotiana

tabacum) (Sierro et al., 2014), pepper (Capsicum annum)(Kim et al., 2014) and petunia

(Petunia hybrida) (Bombarely et al., 2016). Genomestructure analysis has revealed highly

conserved micro- and macrosynteny between many of thesespecies (Kim et al., 2014;

Sierro et al., 2014; Ranjan et al., 2012; The Tomato GenomeConsortium, 2012; Kimura and

Sinha, 2008a). The reason for this is the absence oflarge-scale duplication events (such as

polyploidization) early in the radiation of the Solanaceae(Matsukura et al., 2008; Doganlar

et al., 2002). The set of available Solanaceae genomesequences (http//:solgenomics.net)

represents a rich reference database for comparativefunctional and evolutionary biology

studies through the analysis of orthologous and paralogousgenes (Fernandez-Pozo et al.,

2015).

Tomato stands out among the Solanaceae, as its biologicalfeatures make it a

convenient model species. It is a diploid (2n = 24) with arelatively small genome

(950 Mb), contained in 12 pairs of large chromosomes thatcan be easily recognized

(The Tomato Genome Consortium, 2012; Matsukura et al.,2008; Rick, 1991). Tomato

plants of most varieties have a relatively short life cycle(between 90 and 120 days) and

are autogamous, a condition for the production oftrue-breeding lines. Its reproductive

biology allows easy manipulation (collection and storage ofpollen, a great number

of floral buds and easy emasculation) forcross-hybridization and production of a high

number of seeds per plant (Carvalho et al., 2011; Kimuraand Sinha, 2008b; Matsukura

et al., 2008; Giovannoni, 2004; Meissner et al., 1997;Rick, 1991; Rick and Yorder, 1988).

Tomato is also richly endowed with numerous mapping traits,QTLs, well-developed

linkage groups, high-density DNA marker collections ofvarious types, including

RFLPs, AFLPs, RAPDs, CAPS, dCAPS, SNPs and SSR (Hirakawa etal., 2013; Shirasawa

and Kirasawa, 2013; Shirasawa et al., 2010; Doganlar etal., 2002; Saliba-Colombani

et al., 2000; Eshed and Zamir, 1995; Tanksley et al.,1992), which are comprehensively

organized in a unified database(https://solgenomics.net/tools/index.pl). The Solanaceae

Genomics Network represents a platform for bioinformaticsanalysis and comparison

of information obtained from various ‘omics’ tools. Thisincludes BLAST for nucleic

acid sequences for analyses of genomics, transcriptomics,proteomics, metabolomics,

interactomics and epigenomics. Tomato research alsobenefits from germplasm banks

(cited above), including a broad array of wild speciesrelatives and numerous landraces,

introgression lines (ILs) and mutant collections which aidthe identification of a large set

of hereditary modifications (The 100 Tomato GenomeSequencing Consortium, 2014;

Ranjan, 2012; Kimura and Sinha, 2008a; Bai and Lindhout,2007; Paran and van der

Knaap, 2007; Emmanuel and Leavy, 2002; Rick, 1991).Finally, the ability for asexual

propagation with regenerative plasticity and theavailability of diverse organ and tissue

culture protocols allow robust and reproducible genetictransformation mediated by

Agrobacterium (Pino et al., 2010; Seguí-Simarro and Nuez,2007; Meissner et al., 1997;

Rick, 1991; McCormick, 1991).

The last decade has seen the ascendance of the dwarfvariety Micro-Tom (MT), a small

and fast-growing tomato cultivar originally bred forornamental purposes (Scott and

Harbaugh, 1989). Its suitability as a genetic model wassubsequently demonstrated,

encouraging its adoption by the plant research community(Campos et al., 2010; Meissner

et al., 1997). Many aspects of plant biology have beeninterrogated using MT as a model,

including, but not restricted to, fleshy fruit developmentand metabolism (Su et al., 2015;

Yin et al., 2010; Akihiro et al., 2008), plant–microbeinteractions (Deganello et al., 2014;

Zsögön et al., 2008), glandular trichome development(Campos et al., 2009), hormone

biology (Zouine et al., 2014; Sagar et al., 2013; Serraniet al., 2007, 2008) and genome

editing (Čermák et al., 2015; Zsögön et al., 2017).

3 Patterns in tomato plant development

3.1 Growth habit in tomatoes

Growth habit is a fundamental aspect of plant architecture,determined chiefly by plant

height, disposition of vegetative and reproductive brancheson the main axis and by the

pattern of side branching. The two basic growth habits aremonopodial and sympodial

(Bell, 2002). The former can be found in the model speciesArabidopsis and Antirrhinum

and is characterized by growth from a single apicalmeristem, which produces a sequence

of leaves until a developmental clue (e.g. photoperiod)leads to its conversion into a floral

meristem. The resulting plant displays two clearlydifferentiated phases: vegetative and

reproductive. On the other hand, most species of theSolanaceae family, such as tomato

and Capsicum, grow vegetatively until an endogenous signaltriggers the conversion of

the apical meristem from vegetative to floral, usuallyafter a relatively constant number

of leaves has been formed. In most tomato cultivars, theapical meristem produces an

inflorescence after 6–12 leaves (Samach and Lotan, 2007).Growth then continues from

the closest axillary meristem below the inflorescence,which produces a module of three

leaves and an inflorescence called sympodium (pl.sympodia). The sequence is repeated

indefinitely, as each sympodium is followed by another oneoriginating from its most

proximal axillary meristem. The vigorous growth of eachsympodium displaces the prior

inflorescence to a lateral position, giving the impressionof a stem growing vertically

through the concatenation of sympodia (Fig. 1a).

3.2 Role of mutations

A spontaneous mutation appeared in Florida in 1914, leadingto a drastic alteration in the

growth pattern described above (Yeager, 1927). The mutantplant showed a progressive

reduction in the number of leaves in each sympodial unit,until vertical growth was

terminated by the appearance of two successiveinflorescences (Fig. 1b) (MacArthur,

1932). Vigorous growth of side branches then ensued,conferring a bushy aspect to the

mutant plant, which was hence named self-pruning (sp). Thedeterminate growth habit

of the sp mutant further combines the agronomicallydesirable compact growth with an

almost simultaneous ripening of all the fruits in theplant. This particular trait allowed

the introduction of mechanized harvest in field-growntomatoes (Stevens and Rick, 1986).

The disadvantage of the sp mutation is that the number ofphotosynthetic sources (i.e.

leaves which export photosynthate) is limited, leading tothe production of fruits with

reduced total soluble solids, a trait of great agronomicimportance for tomato quality

(Rousseaux et al., 2005; Emery and Munger, 1970).Nevertheless, beginning in the 1960s,

the sp mutation was bred into a great number of field-grownprocessing tomato cultivars

whose fruits are used in the production of ketchup, sauces,soups and extracts, among

others (Hanna et al., 1964).

Cloning and molecular characterization of the SELF-PRUNING(SP) gene revealed

it to be an orthologue of CENTRORADIALIS (CEN) and TERMINALFLOWER-1 (TFL1),

which regulate flowering in Antirrhinum and Arabidopsis,respectively (Pnueli et al.,

1998). Further work placed SP as a member of the CETS(CENTRORADIALIS, TERMINAL

FLOWER 1 e SELF-PRUNING) gene family ofphosphatidyl-ethanolamine binding

proteins, which function in diverse signalling pathways inbacteria, animals and plants

(Lifschitz et al., 2014; McGarry and Ayre, 2012;Carmel-Goren et al., 2003; Pnueli et al.,

1998). The large number of proteins interacting with CETSproteins suggests that they

function as adaptors in signalling or as part oftranscription complexes (Wickland and

Hanzawa, 2015; Pnueli et al., 2001). One class of molecularpartners of CETS proteins are

the adapters 14-3-3, which participate in multipleprocesses of cellular signalling (Denison

et al., 2011). In tomato and other members of theSolanaceae family, such as potato and

Capsicum (Kim et al., 2014). The SP3D locus corresponds tothe SINGLE FLOWER TRUSS

(SFT) gene, which is the orthologue of the floweringregulator FLOWERING LOCUS T (FT)

in Arabidopsis (Lifschitz et al., 2006, 2014).

3.3 Role of the SINGLE FLOWER TRUSS (SFT) gene

The SFT gene product is a universal floral inducer whosefunction appears to be conserved

in all angiosperms species studied (Turck et al., 2008).The SFT peptide is a non-autonomous

flowering signal produced in leaves and translocated to thevegetative shoot apex, where

it triggers the transition to reproductive growth (Shalitet al., 2009). Upon entering the

cell cytosol, the peptides interact with 14-3-3 adapters

and move to the nucleus, where

they link with bZIP-type transcriptional activators to formthe Florigen Activating Complex

Figure 1 A schematic depiction of growth habit in thetomato and its wild relatives. (a) Indeterminate

growth, found in all wild relatives of tomato and in mostgreenhouse tomato cultivars. This growth

habit is characterized by the reiterative production ofsympodia (modules of two/three leaves and

one inflorescence), here represented in blue/grey numbers.A functional allele of the CETS family

gene SELF-PRUNING (SP, the orthologue of TFL1 inArabidopsis) is responsible for this growth

type. (b) represents determinate growth plants, resultingfrom a non-functional allele of SP. Vertical

vegetative growth is terminated in two inflorescences upona progressive reduction of the number

of leaves in each successive sympodial unit. Allelicvariation in other members of the CETS family

can lead to (c), a variation on the determinate growththeme where vegetative growth is extended

before termination and variation in the number of leavesper sympodium can occur. Side branching

has been omitted for the sake of clarity, but it has beenshown that determinate plants can branch

more profusely than indeterminate ones. Source: Adaptedfrom Fridman et al. (2002).

(FAC), which promotes transcription of floral meristemidentity genes (Toaka et al., 2011,

2013). SFT has thus been equated to ‘florigen’, ahypothetical systemic signal capable of

inducing flowering, postulated originally for photoperiodicspecies (Lifschitz and Eshed,

2006; Evans, 1971). SFT interacts in a complex fashion withSP, as SFT produces a signal of

systemic termination which induces (or creates a permissiveenvironment for) the transition

from vegetative to the reproductive stage. SP and itsorthologues, on the other hand,

promotes vegetative growth and anti-termination of apicalmeristems (Wickland and

Hanzawa, 2015; Lifschitz and Eshed, 2006). The productionof successive sympodial units

formed by three leaves and an inflorescence in wild-type SPplants, in contrast to the

progressive reduction in leaf number the sp sympodium,suggests that SP and SFT are

not simply antagonists, but that their function arises outof a fine molecular balance (Jiang

et al., 2013; McGarry and Ayre, 2012). Tomato plants mutantfor SP and heterozygous

for a mutation in SFT (sp/sp; SFT/sft) produce a greaternumber of inflorescences and of

flowers per inflorescence, which along with increasedindividual fruit size leads to a 60%

higher yield, when compared to control plants (sp/sp;SFT/SFT) (Krieger et al., 2010).

Although originally described as ‘single-gene heterosis’,it was later shown that the basis

for increased yield was a readjustment of thevegetative-to-reproductive growth balance

(Vicente et al., 2015), probably based on the dosage of‘florigen’ (Jiang et al., 2013).

Allelic variation for SFT from wild tomato relatives canlead to dramatic changes in plant

architecture (Fig. 2). More recent work has shown thatmutations in other genes coding

for components of the FAC can also lead to alterations inplant determinacy with direct

impact on plant yield and fruit quality (Park et al., 2014).

The evolution of SFT homologues into flowering repressorshas been well documented

in various species (Pin and Nilsson, 2012; Wickland andHanzawa, 2015). In tomato, the

SP5G paralogue controls earliness in flowering and sidebranching. The allele from the

wild relative of tomato Solanum pennellii (discussed inlength below) causes delayed

flowering and increased height and dry mass whenintrogressed into cultivated tomato

of the determinate type (sp/sp) (Jones et al., 2007).Increased growth is brought about by

greater internode length and a larger number of nodesbetween successive inflorescences,

instead of the premature termination characteristic ofsp/sp plants (Fig. 2c). The resulting

growth habit is a variation on the determinate growth themeand has been termed

‘semi-determinate’, as it represents an extension ofvegetative growth (Fig. 1c). Fridman

et al. (2002) also described semi-determinate growthproduced by natural variation in

the CETS family paralogue SP9D. Determinate plants (sp/sp)harbouring the S. pennellii

allele of SP9D produce an average of eight inflorescenceson the main shoot, with two

leaves between inflorescences, compared to fiveinflorescences and one intervening leaf

in the isogenic sp/sp cultivar (Fridman et al., 2002). Theincreased leaf area represents

a stronger source of photosynthate to the fruits, resultingin higher total soluble solid

contents (Brix). The effects of the SP6A paralogue have notbeen studied in tomato, where

a premature stop codon interrupts the protein codingsequence, making it non-functional

(Carmel-Goren et al., 2003). In potato, however,constitutive expression of the orthologue

StSP6A induces tuberization under non-inducingenvironmental conditions (i.e. long days),

whereas silencing of the gene precludes tuberization inshort days (Navarro et al., 2011).

Taken together, these results imply that the CETS family intomato is not only relevant for

the control of flowering, but rather as an integrator ofthe balance between vegetative

and reproductive development (McGarry and Ayre, 2012). TheCETS gene family therefore

represents a promising target for breeding efforts in theSolanaceae family, particularly

for tomato and potato (Abelenda et al., 2014). Theunderlying molecular mechanisms

whereby these genes control plant development are thesubject of intense research by the

plant community, but a comprehensive picture is still notforthcoming.

4 Water relations in tomato

Agriculture consumes as much as 70% of the freshwater inthe planet. Population growth,

along with increased urbanization, will lead to competitionfrom industrial and domestic

water users (Connor and Stoddard, 2012). Climate change hasbeen predicted to alter

rainfall patterns and is thus likely to affect rainfedagriculture, which accounts for 80%

of the world’s arable crop land. Crop scientists musttherefore endeavour to, on the

one hand, increase the total agricultural output using thesame or a reduced amount of

irrigation water and on the other, develop crops withimproved tolerance to water scarcity

and with better yield under conditions of unreliable watersupply.

Water is the most limiting and yet the most abundantlyneeded resource by plants to

grow and function efficiently, as it makes up most of themass of plant cells. In each cell,

the cytoplasm accounts for only 5–10% of the cell volume,whereas the remainder is a

large water-filled vacuole. Water forms a continuum betweenthe soil, the plant and the

atmosphere, and the combined effects of the soil and theatmosphere can effect changes in

the water status of the plant. Water uptake is conditionedby the structure and biophysical

properties of the soil, and the root system develops tooptimize the relationship between

carbon investment and water and nutrient uptake. Water lossfrom the plant is affected

by evaporative demand (which is in turn determined by thecombination of atmospheric

humidity and temperature). The plant can adjust itsinternal hydraulic conductance, leaf

area, stomatal patterning and function to reduce water losswhile minimizing the impact

on carbon gain. The multiple layers of control of water

relations are therefore deeply

embedded within the developmental programme of the plant.It is no surprise that

Figure 2 Natural genetic variation for genes of the CETSfamily alters tomato plant architecture.

In each picture the plant on the left is tomato cultivarMicro-Tom (MT), a plant with determinate (sp/sp)

growth habit. On the right: (a) sft mutant; the plant lacksthe key floral inducer SINGLE FLOWER TRUSS

and thus displays extremely vegetative growth habit. (b) AMT tomato line harbouring the SFT allele

from the wild tomato relative Solanum pennellii leads to anextreme reproductive phenotype. (c) A line

harbouring the SP5G paralogue from Solanum pennellii in MT.

progress in understanding the physiology and biochemistryof plant–water relations has

been inordinately slow.

4.1 Water-use efficiency (WUE)

Water relations in plants can be studied from twodifferent, and sometimes conflicting,

perspectives (Blum, 2005). One is related to theunavoidable trade-off between carbon

fixation and transpirational water loss, as both carbonuptake and transpiration occur

through the stomata. Water-use efficiency (WUE) thus refersto the amount of CO 2 fixed

per unit H 2 O transpired by the plant (Yu et al., 2004;Zhao et al., 2004; Howeel, 2001). WUE

can be defined as long term (WUE lt ), to includerespiratory carbon losses and cuticular

water loss, and is generally used agronomically as theratio of biomass or crop product

(e.g. seed or fruit biomass) and water transpired over thegrowth period (Tambussi et al.,

2007; Viets, 1962). Short-term WUE, is studied at the leaflevel and can in turn be broken

down into instantaneous or intrinsic WUE. The latter (WUEintrinsic ) refers to the relationship

to CO 2 assimilation (A) and stomatal conductance to H 2 Ovapour (g s ), without taking into

account evaporative demand from the atmosphere. The former(WUE instantaneous ), on the

other hand, is determined as the ratio of A totranspiration (E), which is calculated as the

product of g s � leaf-to-air vapour pressure deficit(VPD). This parameter is more usually

called transpiration efficiency (TE) and represents thegenetic component of WUE (Vadez

et al., 2014).

Long-term WUE in plants is negatively correlated withcarbon isotope discrimination

(Δ 13 C), as shown by Farquhar et al. (1982, 1989).Ribulose-1,5-bisphosphate carboxylase/

oxygenase (Rubisco) catalyses preferentially the fixationof the 12 C carbon isotope as

opposed to the heavier 13 C. Such ‘discrimination’ againstthe heavier isotope is stronger

when gas exchange between the leaves and the atmosphere isnot a limiting factor for

carbon assimilation. In conditions restricting stomatalopening, such as reduced water

supply or increased water demand, the concentration of CO 2in the sub-stomatal cavities is

reduced and the relative assimilation of the 13 C isotopeincreases proportionally (Condon

et al., 2002; Brugnoli and Farquhar, 2000; Farquhar et al.,1989; Martin and Thorstenson,

1988; Farquhar et al., 1982). Since the drop in carbonfixation is not as strong as the drop

in water loss, an increase in WUE occurs and can bedetermined indirectly measuring

Δ 13 C in plant material of interest. Δ 13 C has thus beensuccessfully established as proxy

for WUE in many crop species, including tomato, but also inArabidopsis, barley, peanut,

sunflower and wheat, among others (Arms et al., 2016;Lounsbery et al., 2016; Wei et al.,

2016; Vicente et al., 2015; Barrios-Masias et al., 2014;Chen et al., 2012; Xu et al., 2008;

Virgona et al., 1990; Farquhar et al., 1989; Hubick andFarquhar, 1989; Hubick et al.,

1986; Farquhar and Richards, 1984). Natural variationexists for Δ 13 C in plants (Des Marais

et al., 2016; Lounsbery et al., 2016; Manzaneda et al.,2015; Viger et al., 2013; Juenger

et al., 2010; Xu et al., 2008; Farquhar and Richards,1984), but the complexity of this trait,

which is developmentally controlled and influenced bymultiple biological parameters, has

hampered efforts to produce more water-use efficient crops(Condon et al., 2004).

4.2 Plant responses to water scarcity

A second aspect of plant–water relations is the response ofplants to water scarcity, either

on the supply side in the soil or on the demand side in theatmosphere (in the form of

high evaporative demand which overtaxes the plant’stranspirational capacity) (Passioura,

2007). The alterations in plant–water relations resultingfrom either reduced supply or

increased demand of water are studied under the nebulousand frequently misused label

of ‘drought’. In agricultural terms, ‘drought resistance’is defined as yield in relation to a

limited water supply (Passioura, 1996). Although episodesof restricted water supply (or

increased demand) lead to an increase in WUE as aconsequence of reduced stomatal

conductance (Franks et al., 2015), the physiological basesof drought resistance and

increased WUE can be quite distinct and are usuallyapproached as separate problems.

An increased understanding of the physiological mechanismscontrolling both WUE and

drought resistance could lead to increases in agriculturaloutput and the avoidance of

massive agricultural losses during episodes of severedrought.

5 Natural genetic variation in tomato

Natural genetic variation is a key resource for both basicand applied research (Nunes-Nesi

et al. 2016). Genetic diversity is the result of smallgenomic changes, either random or

derived from natural selection (or from human selection inthe case of domestication).

Naturally occurring genetic variation is generallyperceived as a better source of genetic

‘options’ in breeding programmes than artificiallygenerated variation (e.g. by induced

chemical or physical mutagenesis) because a certainselective pressure has already

acted on the fitness of the organism (Alonso-Blanco et al.,2005). Dissecting the genetic

variation of a species can yield a large amount ofinformation with functional, ecological

and evolutionary significance for developmental andphysiological studies (Alonso-Blanco

et al., 2009; Koornneef et al., 2004) and has strongimplications for breeding programmes

in crops of economic importance, including tomato, Solanumlycopersicum (Gur and

Zamir, 2004). It is estimated that more than 7500 tomatovarieties exist in the world today,

yet their genetic basis is extremely narrow as a result ofartificial selection, which focused

mostly on fruit-related traits (Korir et al., 2015; Bauchetand Causse, 2012).

5.1 Genetic variation and resistance to abiotic stresses

The tomato is closely related to another 12 species (asub-sample depicting leaf and

floral variation between them is illustrated in Fig. 3)which were all previously part of the

genus Lycopersicon (Taylor, 1986; Rick, 1976, 1983).Although they share certain traits

such as laterally dehiscent anthers and pinnate leaves,molecular phylogenetic analysis of

tomato and its relatives led to their placement back in theoriginal Linnean clade, genus

Solanum (Caicedo and Peralta, 2013). All members of thisgroup are diploid species with

12 chromosomes (2n = 2x = 24) which share a large degree ofsynteny with one another.

Their distribution ranges from southern Ecuador, includingthe Galápagos Islands, through

Peru to northern Chile. This large area encompassesdrylands, areas of high altitudes with

low night temperatures and coastal areas affected by highsalinity (Taylor, 1986). Each

species is adapted to a particular habitat and thus offerattractive genetic variation for

breeders aiming at broadening the relatively narrow geneticpool of tomato (Warnock,

1991). Solanum galapagense, for instance, is endemic to theGalápagos Islands and

is sometimes found as close as 5 m above the high tide line(Rick, 1973). There, it is

continuously exposed to salt spray and salt accumulation inthe soil, so it is considered

a potential source of genes for salt tolerance (Tal andShannon, 1983; Rush and Epstein,

1976). Solanum habrochaites is found in a strip of centralPeru at altitudes ranging from

500 to 3500 m above sea level. Whereas cultivated tomato isgenerally susceptible to

temperatures lower than 10°C, chilling-resistant ecotypesof S. habrochaites have been

found, dwelling in high-elevation areas where nighttemperatures can drop to as low as

5°C (Patterson, 1988; Patterson and Payne, 1983). S.habrochaites is also the most notable

source of arthropod resistance, although few genes or QTLshave been characterized at

the molecular level controlling this trait and littleprogress has been made in breeding

these into cultivated tomatoes. It has recently been shownthat overexpression of

S. habrochaites genes in tomato can lead to significantincreases in tolerance to multiple

abiotic stresses (Liu et al., 2015a,b).

5.2 Genetic variation and drought resistance

The cultivated tomato is mesophytic, and thus, is notsignificantly resistant to episodes of

drought. The main sources of genetic variation for droughtresistance are the green-fruited

wild relatives S. chilense and S. pennellii (Rick, 1973).Whereas the former is adapted to one

of the most arid environments on the planet, the Atacamadesert (Maldonado et al., 2003),

the latter dwells in a narrow strip of 500–1500 m elevationin the Peruvian Andes, where

the soil is usually dry but the weather is mild (Rick,1973). Individuals of S. chilense display

gametophytic self-incompatibility, so they are exclusivelyoutbreeders (Rick and Lamm,

1955). There are also several barriers to crosses with thecultivated tomato (Martin, 1961).

Few seeds are viable and only crossing male S. chilenseplants with female S. lycopersicum

yields enough viable seeds to attempt embryo rescue (Chenand Imanishi, 1991). Drought

resistance in S. chilense is not derived from shoot traits,as its bipinnate, fern-like leaves

lose water as rapidly as the cultivated tomato leaves whendetached, and have a similarly

low ability to withstand desiccation in the entire plant(Rick, 1973). Instead, the drought

resistance of this wild species involves the production ofextremely long roots which grow

deep into the rocky desert soil to reach the water tables(Rick, 1973). The root:shoot ratio

Figure 3 A sample of the natural variation in tomato. Fromleft to right, representative leaf and

inflorescence of: S. peruvianum (LA0153), S. neorickii(LA0247), S. pimpinellifolium (LA0373),

S. lycopersicum var. cerasiforme (LA0292), S. chilense(LA1930), S. chmielewskii (LA1028), S. pennellii

(LA706), S. lycopersicum cv. M82 (LA3475).

is increased under drought, as more resources are allocatedto root development and less

to stems and leaves (Avramova et al., 2016; Xu et al.,2015; Vadez et al., 2007; Chen and

Tabaeizadeh, 1992). The large investment of S. chilense inroot biomass is an interesting

research avenue, as significant gains in crop productivityhave been achieved in semi-arid

regions by breeding for increased root depth (Fischer andTurner, 1978). Several drought

responsive genes have also been characterized in S.chilense (Chen et al., 1993, 1994;

Frankel et al., 2003; Yu et al., 1998). Nevertheless, aswill be argued in the following

section, the wild relative of tomato showing the greatestpromise for breeding of drought

resistance in tomato is Solanum pennellii (Rick, 1973;Rudich and Luchinsky, 1986).

6 Case study: Solanum pennellii as a source ofdrought-resistance

Solanum pennellii grows in the exceedingly dry westernslopes of the Andes, most of its

area of distribution lies in rain shadow (Warnock, 1991).Throughout its habitat, however,

S. pennellii experiences frequent periods of fog, so it hasbeen proposed that the plants

can take up a certain amount of water from the atmosphere(Rick, 1973). Its leaves are small,

thick and round, and of a light green colour and stickytexture (Holtan and Hake, 2003).

They also have the peculiarity of a roughly equalproportion of stomata on the upper and

lower leaf surface, as opposed to tomato, where most(usually >70%) stomata are found

on the lower, or abaxial, surface (Kebede et al., 1994; Gayand Hurd, 1975). S. pennellii

has thin, branched roots which grow superficially andamount to less than 5% of the

proportional weight in S. lycopersicum (Yu, 1972). CharlesRick first showed that S. pennellii

can be crossed with the tomato, producing a fertileinterspecific hybrid (Rick, 1960). The

interspecific hybrid produces a large root system, whichgrows to a greater depth and

explores a greater volume than the cultivated parent(Rudich and Luchinsky, 1986).

Plant biologists have been showing increasing interest inS. pennellii in recent years,

and it is the latest wild relative of tomato to have itswhole nuclear genome sequenced

(Bolger et al., 2014). Plant breeders have long beenattracted to this species as a potential

source of drought resistance and other useful traits. Itsleaves are profusely covered with

glandular hairs which secrete sticky exudates conferringresistance to insects such as the

potato aphid (Gentile and Stoner, 1968) and red spider mite(Gentile et al., 1969). A major

technical breakthrough was the development of a collectionof S. pennellii introgression

lines (ILs) in tomato (Eshed and Zamir, 1995). It consistsof 76 lines containing a defined

genomic segment of S. pennellii (LA0716) replacinghomologous regions in a tomato

(S. lycopersicum cv. M82) background. The S. pennelliisegments are overlapping between

lines and adding them up in the 76 lines covers the wholegenome of the species.

Physiological analysis of the whole population thereforeallows mapping QTLs and genes

of interest and this has been successfully achieved formany traits (Fanourakis et al., 2015;

Chitwood et al., 2014; Arikita et al., 2013; Ron et al.,2013; Gorguet et al., 2008; Fridman

et al., 2002). Similar collections of ILs were latergenerated for the species S. habrochaites

f. hirsutum (LA1777); S. lycopersicoides (LA2951) e S.pimpinellifolium (TO-937) (Barrantes

et al., 2014; Canady et al., 2005; Monforte and Tanksley,2000).

The hallmark of S. pennellii is its remarkable ability towithstand water deprivation in the

soil (Fig. 4). Yu (1972) was the first to explore someaspects of water relations in S. pennellii.

He showed that the water content in fresh S. pennelliitissue is considerably higher

than in a tomato cultivar (VF-36). He also proved that thedifference in water loss from

detached leaves was negatively correlated with stomataldensity, and thus, concluded that

regulation of stomatal opening could be the key factordetermining water use. Heterotic

performance was observed for the F 1 interspecific hybrids

of S. pennellii and tomato for

water-use efficiency (WUE) and for the percentage of waterloss from detached leaves (Yu,

1972). The latter was decreased and the former increased inthe hybrid with respect to

either parent. One further study compared water relationsof the tomato, S. pennellii and

their mutual F 1 , confirming several of the observationsmade by Yu (Cohen, 1982). The

drought resistance of S. pennellii has also been studied atthe genetic and biochemical

level. Kahn et al. (1993) showed that in detached leavesthat were wilted to 88% of their

fully turgid weight, S. pennellii maintained a higher leafwater potential and accumulated

less ABA than did S. lycopersicum or hybrids of the twospecies.

Drought-responsive genes have been cloned from S.pennellii, which encode proteins

as H1 histone (Wei and O’Connell, 1996), lipid transferproteins (Treviño and O’Connell,

1998); Early Responsive to Dehydration 15 (ERD15), anegative regulator of ABA (Ziaf

et al., 2011); and universal stress protein (USP)(Loukehaich et al., 2012). O’Connell

et al. (2007) suggested that the drought-induced H1 histoneregulates changes in gene

expression in response to drought stress, whereas the lipidtransfer proteins act at the

deposition of thicker wax layers. Overexpression of SpERD15in transgenic tobacco plants

Figure 4 Resistance to wilting in S. pennellii. Plants ofS. pennellii (left) and tomato cv. M82 (right) were

grown in the same pot, hence sharing soil with similarwater availability. At the stage of seven leaves,

water was withheld and the photograph taken five dayslater. Height of pot: 25 cm.

enhances tolerance to multiple abiotic stresses (e.g.drought, cold and salt stress) by

the increased expression of stress-related genes (Ziaf etal., 2011). The SpUSP gene can

have an important role to play in the drought tolerance oftomato and can interact with

an annexin protein, which appears to be involved in thedrought response by an ABA

dependent pathway (Loukehaich et al., 2012;Konopka-Postupolska et al., 2009).

Other researchers later confirmed that S. pennellii alsohas a higher WUE (Martin

et al., 1999; Kebede et al., 1994), defined as the amountof carbon fixed by the plant

per unit of water transpired (Yu et al., 2004; Zhao et al.,2004; Howeel, 2001). This trait

is under genetic control, and F 1 plants of crossesbetween S. pennellii and cultivated

tomato showed intermediate WUE values between the parents(Martin and Thorstenson,

1988). Three QTL-controlling WUE were identified (Martin etal., 1989) and subsequently,

screening the IL population of S. pennellii using Δ 13 C asa proxy for WUE, a QTL was

detected in the introgression line IL5-4 (Xu et al., 2008).Interestingly, this line harbours

the S. pennellii allele of the CETS family gene SP5G, whichleads to semi-determinate

growth habit (Jones et al., 2007; Fig. 1c). Anotherinteresting genetic variant found in

the IL5-4 is the functional allele of the OBSCURAVENOSA(OBV) gene (Barrios-Masias

et al., 2014; Jones et al., 2007). OBV controls thedevelopment of a structure connecting

the vascular bundle with the epidermis known as bundlesheath extension (BSE),

which is involved in various physiological processes at theleaf level, including, but not

restricted to, leaf hydraulic conductance and lighttransmittance (Buckley et al., 2011;

Sommerville et al., 2012; Liakoura et al., 2009;Karabourniotis et al., 2000). The OBV

gene is not functional in the tomato cultivar M82 used asgenetic background for the

ILs (Jones et al., 2007). Zsögön et al. (2015) carried outa process to create near-isogenic

lines (NILs) for the OBV phenotype. This represents adifferent approach to the use of

ILs and consists of the controlled introgression of avisually identifiable phenotype into

a model tomato cultivar (Carvalho et al., 2011; Maxon-Smithand Ritchie, 1983). Briefly,

after an initial hybridization between tomato and a relatedwild species, a series of back

crosses to tomato is performed in subsequent generations,selecting each time for the

phenotype of interest. The resulting lines arenear-isogenic (hence NILs) to the original

tomato parent. NILs with either a functional or a mutantallele of the OBV gene showed

significant differences in leaf anatomy and water relations(Zsögön et al., 2015). Stomatal

conductance and leaf hydraulic conductance (K leaf ) were

decreased by the absence of a

BSE (i.e. harboring the recessive obv allele); however,long-term WUE was not affected.

Barrios-Masias et al. (2014) suggested that both SP5G andOBV could act synergistically to

control water relations in tomato. An alternativeinterpretation currently under exploration

is the possibility that SP5G, as well as other paraloguesof the CETS gene family, affects

water relations in tomato indirectly through their effectson plant growth habit.

7 Plant development and water relations

Genetic diversity for WUE has also been explored in thewild relative S. habrochaites

f. hirsutum. Two NILs harbouring chromosome 9 segments ofdifferent sizes from that

species in tomato were shown to increase WUE compared tothe tomato control (Goodstal

et al., 2005; Truco et al., 2000). Further study of bothNILs led to the characterization

of a QTL (stm9), responsible for the maintenance of plantshoot turgor upon chilling of

the root system (Easlon et al., 2014). Two QTLs controllingΔ 13 C were recently described

in chromosome 9, suggesting the existence of a complexgenetic control of WUE

(Lounsbery et al., 2016). Interestingly, the peak value ofone of the QTLs, explaining 70%

of the phenotypic variation, co-localized with a geneticmarker (T0532_Solyc09g009020)

positioned very close (52 genes upstream) of the SP9Dlocus, another member of the CETS

gene family (www.solgenomics.net). As stated above, the

SP9D from S. pennellii leads to

a semi-determinate growth habit, but the effect of the SP9Dallele from S. habrochaites

f. hirsutum on plant architecture has not hitherto beendescribed.

The controlled introgression of delayed wilting upon waterdeprivation from S. pennellii

into tomato cv. Micro-Tom led to the characterization of aline with increased WUE

(Zsögön, 2011). Genetic mapping showed that theintrogression carries a relatively large

(42–54 cM) S. pennellii chromosome 1 segment, which waslater narrowed down to

3.2–19 cM. The QTL was named Water Economy Locus inLycopersicum (WELL). Both

the original line and sub-line showed a semi-determinategrowth habit and increased

long-term WUE as determined by Δ 13 C. Interestingly, twouncharacterized paralogues

of the CETS family (Solyc01g009560 and Solyc01g009580) arecontained in this region,

although their expression levels appear to be low, both intomato and in S. pennellii (José

Jiménez-Gómez, personal communication). Further workcomparing tomato lines with

determinate, indeterminate and semi-determinate growthshowed that the latter exhibit a

higher long-term WUE, assessed both directly as biomassgained per unit water transpired

and indirectly via Δ 13 C (Vicente et al., 2015).Significantly lower Δ 13 C values (more than

1.0‰ difference) were found in all semi-determinate lines(WELL and heterozygote sft

mutants in an sp/sp background) compared to determinate(sp/sp) and indeterminate

ones (SP/SP). This translates into a higher leaf-level WUEfor semi-determinate lines, which

was confirmed through gravimetric determination of drymatter gain versus transpired

water, that is, long-term WUE. The results showed goodagreement between Δ 13 C and

direct determination of WUE.

Increased WUE in semi-determinate tomato lines could be afunctional consequence

of the adjustment of the vegetative-to-reproductive balancein plant organs with different

transpiration and CO 2 assimilation capacities. Morespecifically, semi-determinate growth

could lead to an optimization of the relationship betweenorgans which ‘spend’ water

while producing photosynthate (mature leaves) and organswhich practically spend water

without net carbon fixation (flowers, fruits, youngleaves). Semi-determinate growth

has been shown to increase fruit yield by similarlyaltering source–sink relationships, as

described for heterozygous sft mutant plants in differentcommercial cultivars (Krieger

et al., 2010). Low yield is found in the homozygous sftmutant (Fig. 2a), in agreement

with the low partitioning of dry matter to reproductiveorgans in this genotype (Vicente

et al., 2015; Krieger et al., 2010). An alternativepossibility is that genes of the CETS

family pleiotropically affect water relations directly andnot through their effects on plant

development. Effects in stomatal conductance have beenreported for FLOWERING

LOCUS T (FT), the Arabidopsis orthologue of SFT (Kinoshitaet al., 2011). This, however, is

just one among the plethora of functions ascribed to FT sofar and has unfortunately not

been explored further (Pin and Nilsson, 2012).


Plant–water relations in terms of drought resistance andwater-use efficiency (WUE) are

usually approached as biochemical or physiologicalprocesses and studied at the leaf level.

Scaling up to the whole plant level is not alwaysstraightforward, as additional levels of

developmental complexity get compounded along the way. Slowaccumulation of evidence

is beginning to shape a new picture where water relationscan be studied within the frame

of whole plant development. Manipulation of plant growthhabit can lead to agronomically

better balances between vegetative and reproductive growth.This was the touchstone of

the Green Revolution, where the yield of cereal crops wasimproved by converting the

overly vegetative tall varieties into well-balancedsemi-dwarf ones (Spielmeyer et al., 2002;

Peng et al., 1999). A similar avenue is opening up forspecies with sympodial growth habit,

of which tomato represents not only an outstanding geneticmodel but also a hugely

relevant cash crop. A possible explanation for thephenotypic effects described in this

chapter is that semi-determinate growth represents a

‘golden mean’ between the overly

vegetative indeterminate and the overly reproductivedeterminate habit. The possibility

of a parallel improvement in drought resistance and WUEthrough the manipulation of

vegetative-to-reproductive balance should be exploredfurther and could lead to novel

and exciting hypotheses concerning the relationship betweenplant form and function.


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6 Chapter 6 Ensuring the geneticdiversity of tomato

Table 2 Major tomato ex situ germplasm collectionsmaintained by selected institutes/gene banks

7 Chapter 7 Tomato plant responses tobiotic and abiotic stress

1 Introduction

By 2050, the world population is expected to reach 9.6billion, and to meet the rising

demands arising out of this, estimates of the Food andAgriculture Organization project

that global food production has to increase by 60%(fao.org). On top of the rising

demand for food, there are several reasons to be concernedabout insufficient global

food production in the future (Rosegrant and Cline, 2003;Schmidhuber and Tubiello,

2007; Brown and Funk, 2008). For instance, climaticprediction models indicate severe

weather pattern changes, which will result in more frequentdroughts and floods, rising

global temperature and decreased availability of freshwaterfor agriculture. Moreover,

arable land is shrinking because of soil erosion, salinityand other soil toxicities (Stocking,

2003). Finally, it is expected that global climate changeswill result in the emergence of

new pest and diseases into production areas previously notaffected. As a result of this

situation, crops will have to thrive in a dynamicenvironment constantly challenged by

changing abiotic and biotic stresses that currently causean estimated yield loss of up to

60% (Seo et al., 2011). Therefore, in addition todedicating efforts to conserve water and

land resources, the current challenge in agriculture is toincrease crop productivity by

improving crop resistance and tolerance to pests, diseasesand environmental stresses,

respectively.

Tomato (Solanum lycopersicum) is one of the most importantvegetables cultivated

worldwide, but its production is threatened by severalpests, diseases and environmental

factors. It is estimated that tomato is susceptible to atleast 200 diseases caused by

viruses, bacteria, fungi and nematodes (Lukyaenko, 1991).Consequently, it is necessary

to develop applied strategies to improve the productionsystem. The most effective

approach to sustainably improve tomato productivity andmarketability is by genetic

improvement for increased resistance to plant pests anddiseases, and tolerance to

environmental stresses.

Tomato belongs to the Solanum sect. lycopersicon, arelatively small clade within the

Solanaceae family consisting of 14 species or subspeciesincluding the cultivated tomato,

S. lycopersicum. The tomato species’ natural habitatencompasses diverse climatic,

geographical and environmental regions, ranging from dryarid zones to humid tropical

rainforests (Moyle, 2008). This habitat diversity hasenormously contributed to the great

variation within the clade. However, the development of newcultivars with enhanced

resistance or tolerance is hindered due to lack of geneticdiversity within cultivated

S. lycopersicum germplasm, because of its domestication and

breeding process (Rick and

Chetelat, 1995). Fortunately, germplasm collections ofrelated wild species with broad

morphological, physiological and metabolic diversity areavailable for researchers, and

have served as the main source for introgression ofagronomic traits including resistance

to pests, diseases, fruit quality and abiotic stresstolerance during the last 80 years (Rick

and Chetelat, 1995; Moyle, 2008).

In this chapter, we summarize the current status andadvances in our understanding of

biotic and abiotic stress responses of cultivated tomatoand its wild relatives. Furthermore,

we discuss future trends in tomato stress biology and itspotential implications for tomato

crop improvement.

2 Tomato responses to biotic stress

2.1 Tomato immune signalling and R-gene-mediated resistance

Disease resistance is often a result of co-evolutionbetween plant and pathogen. As the first

line of defence, plants deploy basal defences, which aretriggered at the entry points of

the host cell such as the apoplasm, plasma membrane andplasmodesmata (Mandadi and

Scholthof, 2012; Schwessinger and Ronald, 2012; Mandadi andScholthof, 2013; Mandadi

et al., 2014). During infection, specialized transmembraneproteins termed ‘pattern

recognition receptors’ are activated to initiate basaldefences via recognition of conserved

pathogen- or microbe-associated molecular patterns

(P/MAMPs) such as chitin, flagellin,

lipopolysaccharides and modified peptides. These basaldefences are also referred to as

P/MAMP-triggered immunity (PTI). The PTI immune responsetypically activates defence

hormone signalling pathways such as salicylic acid (SA),jasmonic acid (JA) and ethylene

(ET) culminating in transcriptional activation of defencegenes, which include defensins,

chitinases, lipases and proteinases. Often, virulentpathogens encode ‘effector’ molecules

that interfere with host PTI defences. To counter theaction of effectors, plants evolved a

second line of defence: effector-triggered immunity (ETI),which uses a distinct class of

nucleotide-binding site–leucine-rich repeat (NBS-LRR)domain-containing proteins. These

resistance (R) proteins recognize, directly or indirectly,specific pathogenic effectors inside

the host cell and trigger localized cell death or necrosistermed ‘hypersensitive response’

(HR) and a long-lasting ‘systemic acquired resistance’(SAR) in the distant uninfected

tissues. When compared to the plant model Arabidopsis,these dynamics and the immune

concepts are not well understood for tomato.

Plant disease resistance (R)-genes encode proteins thatrecognize, directly or indirectly,

avirulent (Avr) proteins of a pathogen and initiate plantdefence responses. Several R-genes

found in wild tomato have been used for tomato cropimprovement. It is estimated that

~40 major traits are present in wild tomato that confer

resistance to different diseases.

Of them, approximately twenty are introgressed intocultivated tomato (Ji et al., 2007;

Robertson and Labate, 2011; Ercolano et al., 2012). Most ofthose resistance traits are

conferred by single dominant R-genes encoding conservedNBS-LRR proteins. Several

researchers have focused their efforts on theidentification of R-genes, with the ultimate

goal of using them in tomato breeding for disease and pestresistance, as well as for

functional genomic studies to understand tomato defencesignalling (Ercolano et al., 2012;

Rosli and Martin, 2015). By employing classical forwardgenetic screening and map-based

cloning approaches, many of these mapped R-genes have beencloned (Ercolano et al.,

2012). The tomato R-genes are often encoded by NBS-LRRproteins that work together

with accessory genes encoding protein kinases.

At the molecular level, one of the well-studied tomatoimmune signalling pathways is

the mechanism of tomato R-protein, Prf, an NBS-LRR protein,and its accessory partner,

Pto, a serine/threonine kinase (Martin et al., 1993;Salmeron et al., 1996; Ntoukakis et al.,

2014). The Prf/Pto protein complex confers resistance tobacterial speck disease caused

by Pseudomonas syringae pv. tomato (Pst) strains possessingthe effector proteins, AvrPto

and AvrPtoB. Genetic and biochemical analysis of Prf, Pto,AvrPto and AvrPtoB proteins

revealed dynamic interactions, phosphorylation and

conformational changes occurring

within the complex. According to the prevailing model, Ptointeracts with Prf at the

N-terminal domain of Prf to form an oligomeric complex,comprising of at least two Pto and

two Prf molecules. One of the Pto molecules recognizeseither AvrPto or AvrPtoB, through

interactions with the catalytic cleft of Pto. The effectorrecognition causes conformational

changes in Pto, and releases it from repression by Prf.Subsequently, the de-repressed

Pto is transphosphorylated by a second (helper) Ptomolecule leading to full activation of

the complex that triggers downstream signalling eventsculminating in HR and resistance.

Similarly, R-genes conferring resistance to insects,especially phloem feeders, have been

identified in different plant species including wheat,melon, Medicago, soya bean and rice

(Klingler et al., 2001; Liu et al., 2005; Li et al., 2006b;Klingler et al., 2009; Zhang et al.,

2009; Zhang et al., 2010). In tomato, the R-gene Mi1.2 hasbeen cloned, characterized and

utilized in commercial cultivars. The Mi1.2 gene,originally introgressed from S. peruvianum

(Smith, 1944), confers resistance to certain isolates ofthe potato aphid, Macrosiphum

euphorbiae (Rossi et al., 1998); the silverleaf whitefly,Bemisia tabaci (Nombela et al., 2003);

the potato psyllid, Bactericera cockerelli (Casteel et al.,2006, 2007); and the root-knot

nematode, Meloidogyne incognita (Smith, 1944). Efforts arestill underway to elucidate the

conserved and unique resistance mechanisms of Mi1.2. TheMi1.2 gene is constitutively

expressed in both roots and leaves. The Mi1.2-mediatedresistance against nematodes in

tomato roots is activated soon after germination. However,resistance in leaves is activated

only upon aphid and whitefly infestation, and in plantsthat are at least five weeks old with

fully expanded leaves (Kaloshian et al., 1995; de Ilarduyaand Kaloshian, 2001; Li et al.,

2006a). Furthermore, Mi-1.2 resistance against nematodesinvolves the induction of HR,

while Mi1.2 resistance against aphids only results inreduction of insect fitness (Kaloshian

et al., 1997; de Ilarduya et al., 2003). At the molecularlevel, although Mi1.2-mediated

resistance to aphids and whiteflies requires SA, it is notclear whether SA plays a dominant

role in resistance against nematodes (Branch et al., 2004;Li et al., 2006a; Bhattarai et al.,

2008). Transcriptomic and proteomic analysis of susceptibletomato without Mi1.2 gene

revealed that SA is the main hormone driving plant basaldefence responses against the

potato aphid but not against whiteflies, while intact JAsignalling is required for nematode

susceptibility (Bhattarai et al., 2008; Coppola et al.,2013; Rodriguez-Alvarez et al., 2015).

These differences in resistance responses suggest thatpest/disease–plant interactions

mediated by Mi1.2 elicit different defence signallingpathways. Finally, Mi1.2 appears

to have adverse effects on the beneficial predator, Oriusinsidiosus, suggesting that the

ecological impacts of R-genes on non-target organisms arewide-ranging and should be

taken into consideration when used in breeding programmesas part of an integrated pest

management programme (Pallipparambil et al., 2015).

3 Tomato responses to abiotic stresses

3.1 Abiotic stress tolerance traits, QTLs and rootstockbreeding

Tomato is grown in a wide range of environments throughoutthe world, including tropical,

subtropical and temperate areas. Although tomato varietiesthat are adapted to these

different climatic conditions exist, production is stillchallenged by severe environmental

stresses such as salinity, drought and extreme temperatures(cold and heat). Similar to

pest and disease resistance, tolerance to abiotic stressesis very limited within cultivated

tomato. Fortunately, due to the wide geographicaldistribution of wild tomato relative

species, genetic tolerance to these stresses can be foundand introgressed from

S. chilense, S. peruvianum, S. pennelli, S. habrochaitesand S. pimpinellifolium. However,

only a few stress-tolerant tomato cultivars have beendeveloped leveraging these wild

tomato resistance traits. This is in part due to thecomplexity of inheritance of those traits

that confer abiotic stress tolerance. Oftentimes, thetraits are controlled by quantitative

trait loci (QTL). QTL refers to loci that encompassmultiple genes governing a particular

agronomical trait; some of these QTLs could involvehundreds of genes. QTLs are

influenced by plant developmental stage and environmentalfactors to ultimately result

in stress tolerance (Foolad, 2007). Mapping of such QTLs isa challenge, yet an invaluable

tool for tomato breeding and understanding of the evolutionof complex traits (Pray, 2008).

Because tolerance to abiotic stresses is often controlledby multiple genes, breeding

efforts have focused on identifying QTL markers linked tothe traits. Several QTL markers

associated with cold, heat, drought and salt toleranceduring germination and vegetative

stages are mapped using either recombinant inbred lines(RIL) or backcross populations

from interspecific crosses between stress-sensitive S.lycopersicum and stress-tolerant

S. pimpinellifolium, S. habrochaites and S. pennelliaccessions (Vallejos and Tanksley, 1983;

Breto et al., 1993, 1994; Foolad and Jones, 1993; Foolad etal., 1997, 1998, 2001, 2003;

Foolad and Chen, 1998, 1999; Foolad, 1999; St Clair et al.,2000; Subbiah et al., 2003).

It is important to note that to develop effective abioticstress tolerances that are active

throughout the tomato developmental stages, multiplestage-dependent stress tolerance

traits need to be pyramided together. This is oftenchallenging, because pyramiding

traits is labour intensive and time-consuming, and requiresscreening of large populations

by either conventional or molecular breeding methods(Takeda and Matsuoka, 2008).

Alternatively, identification of abiotic stress tolerancetraits that are active throughout the

plant development can be useful to facilitate thedevelopment of robust stress-tolerant

cultivars. Similarly, genes conferring resistance tomultiple stresses can alleviate the

need to introgress different tolerance factors into thebreeding lines. Foolad et al. (2003)

reported a set of genes that confer tolerance to cold, saltand drought stress in a BC 1 F 1

segregating population from the cross of S. lycopersicum XS. pimpinellifolium by selecting

for rapid seed germination on stress-imposed plants. As thesame trait confers resistance

to multiple environmental stresses, it is possible toperform phenotypic selections using a

single stress factor.

Even though introgressing stress tolerance traits from wildspecies presents opportunities

for tomato genetics and breeding, its utility is stilllimited because it is time-consuming

and expensive (Cuartero et al., 2006; Foolad, 2007).Additional approaches do exist that

can be leveraged to improve abiotic stress tolerance on thefield. One approach is by

the use of tolerant rootstocks for tomato grafting, becauserootstocks can increase crop

tolerance to environmental stresses in several ways. Forexample, rootstocks can indirectly

improve general plant vigour as a result of more efficientnutrient/water uptake and by

conferring resistance to soil pathogens. Recently, it hasbeen shown that tolerant tomato

rootstocks, developed from a cross between salt-sensitiveS. lycopersicum var. cerasiforme

and a salt-tolerant S. pimpinellifolium (or S.cheesmaniae), were able to increase fruit

yield under saline conditions (Estan et al., 2009; Asins etal., 2010; Asins et al., 2015).

Furthermore, by measuring physiological components of thescion, it was shown that the

salt tolerance trait of the rootstock was heritable (h 2 ~0.4 or higher) and is governed by

at least eight QTLs. Most of these rootstock-mediatedimprovements in fruit yield under

saline conditions are the result of the ability of therootstock to reduce changes in scion

water status. As rootstocks also influence levels ofsoluble solids in the fruit, rootstock

breeding offers another opportunity to increase fruitquality traits when plants are exposed

to moderate salinity levels (Asins et al., 2015). It isimportant to note that these strategies

do require some additional resources including graftingfacilities and personnel to select

for best rootstocks and scions, and assess theircompatibilities (King et al., 2010). Finally,

rootstock grafting may be preferred to circumvent theintroduction of undesirable traits as

a result of genetic drag on breeding populations,particularly when utilizing wild species

as resistance source.

3.2 Regulation of gene expression in response to abioticstress

In order to improve tomato stress responses, it is alsonecessary to understand how

the plants respond to environmental stress at multiplelevels from gene expression

regulation to the effects on protein synthesis/degradation,and on the plant metabolic

profiles (Shanker et al., 2014). Currently, efforts areunderway to perform genome-wide

characterization of transcription factors involved inabiotic stress responses and regulation.

At least 112 ethylene response factors (ERF), 69 basicleucine zipper (bZIP) and 81 WRKY

transcription factors have been identified in tomato(Sharma et al., 2010; Huang et

al., 2012; Li et al., 2014, 2015). Functional analyses ofsome of those stress-responsive

transcription factors have confirmed their role in cold,heat, salt and mechanical stress

regulation. For example, several tomato C-repeat bindingfactors (CBF), that belong to

the ERF of family transcription factors, are induced undercold and drought conditions in

wild tomato species (S. peruvianum and S. chilense) makingthem a good target to induce

tolerance using genetic engineering approaches (Mboup etal., 2012).

In addition to transcription factors, microRNAs, a class ofnoncoding small RNAs

involved in post-transcriptional regulation of severalbiological processes including plant

growth, development and stress responses have beencharacterized for their role during

cold stress in tomato (Cao et al., 2014). Approximately, 49miRNAs appear to be regulated

in response to cold stress (Cao et al., 2014). The miRNA

targets include conserved stress

responsive genes such as scarecrow-like proteins andribosomal proteins. The role of

epigenetic modifications in tomato stress responses isstill under investigation. A study

reported that stress causes the removal of demethylation ofregulatory regions of Asr2, a

gene involved in drought response (Gonzalez et al., 2013).Furthermore, it was observed

that epigenetic modifications could be stably inherited tonew progeny, indicating that

epigenetic processes can be leveraged for crop improvementby either biotechnology

(see Chapter 10 of this book) or epigenome breeding viaselection of desirable epialleles.

4 Stress signalling and stress regulatory networks

Despite the significant progress in understanding themechanisms of tomato biotic and

abiotic stress signalling, and the role of phytohormones(SA, JA, ET and abscisic acid) and

secondary messengers (Ca 2+ and reactive oxygen species[ROS]), several questions still

persist. For example, how does tomato integrate diversebiotic and abiotic stress signals

in a dynamic environment? What are the convergence pointsfor the overlapping stress

signal transduction pathways? What are the gene regulatorynetworks underlying diverse

stress signalling in non-model crop plants?

Plant central stress regulators (CSRs) are an emergingsignalling concept, where a few

core genes respond to and integrate multiple stress signalsto impart tolerance against

diverse a/biotic stresses. For example, in Arabidopsis, anR2R3 MYB transcription factor,

BOTRYTIS SUSCEPTIBLE1 (BOS1) mediates tolerance to diversepathogens (Botrytis

cinerea, Alternaria brassicicola, Pseudomonas syringae pvtomato and Peronospora

parasitica), as well as abiotic stresses caused by waterdeficit, salinity and oxidative

stress, possibly by influencing ROS homeostasis (Mengisteet al., 2003). Similarly,

Arabidopsis NPR1, members of snf1-related kinases (SnRK,KIN10 and KIN11), bZIP

family of transcription factors (bZIP2 and bZIP11),modulate transcription of numerous

genes in response to sugar, energy deprivation and diversestresses, enhancing overall

plant stress tolerance (Baena-Gonzalez et al., 2007; Hansonet al., 2008; Balderas

Hernández et al., 2013).

In Arabidopsis, a CSR, BT2 has been well-characterized (Renet al., 2007; Mandadi et al.,

2009). The BT2 protein contains a BTB/POZ domain, andbelongs to a family of five proteins

with similar domain architecture (Du and Poovaiah, 2004).In addition to the N-terminal

BTB/POZ domain, BT2 has two other protein–proteininteraction domains: a central TAZ

domain and a C-terminal calmodulin-binding domain (CaMBD)(Du and Poovaiah, 2004;

Gingerich et al., 2005). BT2 responds to multiple bioticand abiotic signals, including light,

circadian clock, phytohormones, and nutrients and isrequired for resistance to ROS, sugar

and Abscisic acid (ABA)-mediated stresses (Mandadi et al.,2009). These results suggest that

BT2 occupies an integral position in a complex signallingnetwork that perceives, integrates

and responds to multiple, and sometimes competing, signals.Strikingly, transcriptome

profiling revealed that BT2 was one of the downstreamtargets of KIN10/KIN11 and bZIP

pathway (Baena-Gonzalez et al., 2007; Hanson et al., 2008).Understanding further the role

of BT2-like genes in tomato will help developmulti-stress-tolerant tomatoes.

In a manner similar to Arabidopsis BOS1, genetic studies intomato identified an

ABSCISIC ACID-INDUCED MYB1 (AIM1) transcription factor(AbuQamar et al., 2009),

which is induced by pathogens, plant hormones, salinity andoxidative stress, and is

required for resistance to many of the same signals, thusacting as an integrator of diverse

biotic and abiotic stress responses. Similarly, in multipleplant species, members of the

a-DIOXYGENASE family (e.g. a-DOX1), that catalyse theoxygenation of fatty acids in

oxylipin biosynthesis, are transcriptionally activated bydiverse abiotic stresses, pathogens

and insects (Ozturk et al., 2002; Koeduka et al., 2005;Bannenberg et al., 2009; Steppuhn

et al., 2010; Vicente et al., 2012). In tomato, a-DOX1(Sla-DOX1), but not Sla-DOX2, is

transcriptionally activated in response to potato aphid(Macrosiphum euphorbiae) feeding,

independent of SA and JA (Avila et al., 2013).

Virus-induced gene silencing (VIGS) of Sla

DOX1 revealed that it is required for basal resistance toaphids via the oxylipin products of

linoleic acid (18:2). Furthermore, a-DOX1 is also requiredfor resistance against the tobacco

hornworm (Manduca sexta) acting through derivatives oflinolenic acid (18:3) in Nicotiana

attenuata and influencing JA-induced defences (Steppuhn etal., 2010; Gaquerel et al.,

2012). Together, these studies suggest that Sla-DOX1participates in resistance against

insects from different feeding guilds, perhaps usingdifferent lipid substrates and defence

hormone signals. Beyond a few examples, the genome-wideidentities of tomato CSRs

remain largely unknown. Future research focused onidentifying and characterizing other

tomato CSRs and the overlapping gene regulatory networkcomponents will be critical for

tomato crop improvement.

5 Future trends

5.1 Breeding and next-generation omics for tomatoimprovement

One of the major constraints in tomato breeding used to bethe lack of a good linkage

map for all traits of interest, and the lack ofhigh-density molecular markers. However,

with the advancements in next-generation sequencing (NGS)tools and the completion

of the reference tomato genome by the tomato genomeconsortium (Potato-Genome

Sequencing-Consortium, 2011; Loveland et al., 2012;Tomato-Genome-Consortium,

2012), as well as the identification of a large panel ofSNPs by high-throughput genotyping

(Sim et al., 2012a,b; Víquez-Zamora et al., 2013), it isnow possible to construct detailed

and accurate linkage maps. The availability of the entiregenome sequence has also

improved our ability to correlate recombination andphysical maps, thus allowing us to

narrow the QTL intervals and to map the underlying gene(s).The genome assembly is also

enabling identification of candidate genes present aroundthe physical position of an SNP

with observed maximum LOD score (Asins et al., 2015).

Advances in NGS and comparative genomics tools have alsopresented new

opportunities to catalogue the complete repertory ofresistance gene homologs in

cultivated and wild tomato, as well as in relatedSolanaceae species such as potato (Jupe

et al., 2012, 2013; Andolfo et al., 2013a,b; Andolfo etal., 2014). Andolfo (2014) employed

resistance gene enrichment and sequencing (RenSeq)approaches to re-annotate about

25% known tomato NBS-LRR genes, as well as to identify 105novel resistance genes

from unannotated regions in S. pimpinellifolium LA1589 andS. lycopersicum Heinz 1706.

Although the in vivo biological roles of these resistancegene homologs need further

elucidation, the information is vital for several studies.For example, by combining existing

genetic data relevant to resistance gene loci, markers andthe NBS-LRR gene annotations,

positional cloning of candidate resistance loci can beaccomplished readily. Further, by

employing comparative genomics approaches, genomic hot spotregions for resistance

genes that are conserved among elite, related and wildSolanaceous species can be

identified. These resistance gene databases are alsovaluable to understand further the

evolutionary dynamics of disease resistance signalling inSolanaceae species.

5.2 Biotechnology and genetic engineering for tomatoimprovement

In recent years, there has been significant progress ingenetic engineering technologies,

which can all be leveraged for developing abiotic andbiotic stress resistance in tomato. A

few of these technologies involve employing transgenicapproaches, as well as genome

editing tools such as the use of CRISPR/Cas9 (Bortesi andFischer, 2015). The benefits of

genetic engineering are multi-fold, including but notlimited to decreased dependency on

pesticides, enhancing yield and quality of crops, andreducing the overall labour and costs

of plant breeding and production (Saker et al., 2011).

The generation of disease resistance using transgeneoverexpression and silencing

approaches started decades ago, and has been highlysuccessful in Solanaceae plants. For

example, transformation of N. tabacum with a Nucleocapsidgene of the tomato spotted

wilt virus (TSWV) generated tobacco lines resistant to TSWV(Herrero et al., 2000). More

recently, tomatoes expressing the insecticidal cry2Ab gene,from Bacillus thuringiensis,

were developed to gain insect resistance (Saker et al.,2011). The transgenic tomato plants

overexpressing Cry2AB toxin conferred resistance tomultiple pests such as American

bollworm (Helicoverpa armigera) and potato tuber moth(Phthorimaea operculella) (Saker

et al., 2011). Similarly, RNA-interference (RNAi) and VIGSmethods are well established

and optimized for tomato reverse genetics (Wu et al., 2011;Avila et al., 2012, 2013). They

are widely used in tomato functional biology, and toimprove tomato resistance against

stresses as well as to improve agronomic qualities. Forexample, RNAi-mediated gene

silencing was successfully used to gain resistance againstmultiple viruses including the

tomato leaf curl New Delhi virus, tomato yellow leaf curlvirus (TYLCV; Omaha, Thailand

and Taiwan strains) (Ammara et al., 2015; Chen et al.,2015; Singh et al., 2015), as well as to

delay fruit ripening and improve fruit processing quality(Gupta et al., 2013). Although such

transgene overexpression and silencing strategies areinvaluable tools for tomato crop

improvement, the degree of resistance and durabilityimparted by the different constructs

is dependent on several factors such as the type oftransgene sequences, transgene length

and dosage, degree of similarity of the transgene and thetarget sequences, stability of

the transgene expression and the expressed levels/activity

of the transgene protein in

subsequent crop generations. Nevertheless, these strategiesare efficient tools to improve

biotic and abiotic stress resistance in several Solanaceaespecies including tomato.

The latest biotechnology and genome-editing technology thathas experienced a

rapid surge in popularity is the CRISPR/Cas9 system. TheCRISPR/Cas9 system is very

simple, yet highly efficient method to generate specificmutations in any gene of interest.

Its applications are tremendous for transgene-free cropimprovement, and for tomato

improvement. Recently, as a proof-of-concept, thistechnology was used to generate

stable gene-edited tomato with targeted mutations in ahomolog of Arabidopsis

ARGONAUTE7 (SIAGO7) (Brooks et al., 2014). The siago7CRISPR/Cas9 mutants are

phenotypically indistinguishable from anotherloss-of-function EMS-derived siago7

mutant. Further analysis showed that the CRISPR/Cas9approach has high mutagenesis

rate of up to 48% in the transgenic plants screened, andthe mutations are stably inherited

to subsequent generations in the absence of the inductiveCRISPR guide RNA (gRNA)

transgene. Furthermore, multiple transient virus-inducedgene editing (VIGE) vectors are

being developed to facilitate rapid gene editing in plantsusing VIGS vectors. The VIGE

systems are useful not only to generate targeted mutationsin plant genes but also to

target virus sequences in order to confer diseaseresistance. For example, a VIGE system

based on the TYLCV was used to induce virus resistance inN. benthamiana against TYLCV,

and demonstrated that the VIGE system can be used todevelop tomato plants resistant

to DNA viruses (Ali et al., 2015b). Similarly, other VIGEsystems based on tobacco rattle

virus, beet severe curly top virus and bean yellow dwarfvirus (BeYDV) exist that can be

successfully used for CRISPR/Cas9-based editing of tomatoin order to confer resistance

to diverse biotic/abiotic stresses (Ali et al., 2015a,b;Baltes et al., 2015; Ji et al., 2015; Yin

et al., 2015).

5.3 Systems biology for tomato improvement

Further improvement of tomato cultivars to resist bioticand abiotic stresses will also

depend on our ability to effectively identify, study andleverage (i) the genetic diversity

present among all existing tomato germplasm resourcesworldwide (cultivated species,

wild species, landraces, etc.) from which new resistancetraits can be selected and

(ii) the latest techniques to transfer or edit theresistance-linked genes and regulatory

elements from the genetic germplasm pool into thecultivated varieties via breeding

and biotechnology. To achieve this, as well as to furtherunderstand tomato’s adaptive

capability and resilience mechanisms under biotic andabiotic stress conditions, we

suggest that it is critical to embrace a holistic systems

biology approach. For biologists,

systems biology is the integrated study of a biologicalsystem at multiple levels (Joyard

and McCormick, 2010). To truly advance tomato stressbiology, it is essential to catalogue

and integrate the information from desirable tomato geneticvariations and germplasm

and study their responses to diverse biotic or abioticstresses at the level of genome,

epigenome, transcriptome, proteome and metabolome, as wellas reveal the interacting

functional networks. Furthermore, this knowledge has to beappropriately translated into

developing stress-resistant and -tolerant cultivars bypromoting collaborative linkages

between basic and applied researchers working in adifferent aspect of tomato biology,

breeding and biotechnology (Fig. 1).


For updated information on genome sequence, annotation,maps (QTL, physical, etc.) and

breeders tools (markers, phenotypes, etc.) in tomato, wildrelatives and other Solanaceae

species please visit The Sol Genomics Network(www.solgenomics.net). The website also

contains information on periodic Solanaceae meetingsincluding disease and genomic

workshops. Germplasm resources including tomato accessions,cultivars, wild-relative

collections, and recombinant inbred populations for bioticand abiotic stress tolerance and

resistance screening can be requested at the C.M. RickTomato Genetics Resource Center

(tgrc.ucdavis.edu), the European Cooperative Programme forPlant Genetic Resources Transcriptome Proteome MetabolomeScreening, bioassays, data mining, bioinformatics andcomputational analysis Identification of candidate genes/traits (Reverse and Forward genetic approaches) Cloningand characterization

Genetic engineering approaches

(Trans- and cis-genics, silencing, over-expression andgenome editing) Marker-trait association Marker assistedselection Conventional plant breeding Biotic and Abioticstress tolerant breeding lines Multi-location field trialsCultivar release TOMATO GERMPLASM GENETIC POOLS 1’ 2’ 1’:Modern cultivars, breeding lines, interspecific RIL, andS. lycopersicum var cerasiforme accessions 2’: Wildspecies accessions aw : Life aw Genome/ epigenome

Figure 1 Schematic representation of the germplasmresources and framework for multidisciplinary

integrative research in order to develop stress-toleranttomato cultivars [Modified from Shanker et al.

(2014) and Stewart (1995)]. Tomato germplasm genetic poolsare represented by decreasing order

of availability, with the modern cultivars, interspecificrecombinant inbred lines and S. lycopersicum

var cerasiforme at the centre and expanding circle havingaccessions of wild tomato species. The aw

designation represents all-‘life’ genetic resourcesavailable through genetic engineering.

(ECPGR, www.ecpgr.cgiar.org) and the U.S. GermplasmResources Information Network

(www.ars-grin.gov).

7 Acknowledgements

This manuscript was supported by Texas A&M AgriLifeResearch start-up funds and grants

to C. A. (FY16 124185-96180) and K. K. M. (FY16124185-96210) and USDA-NIFA-AFRI

(2015-67030-24294) to K.K.M.

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8 Chapter 8 Developments in tomatobreeding: conventional and biotechnologytools

1 Introduction

Plant breeding is often described as the art and science ofaltering the genetic makeup

of plants for the benefit of humankind (Acquaah, 2012). Asa science, genetics is the

basis for plant breeding, which started soon after therediscovery of Mendel’s laws at

the beginning of the twentieth century. As an art,selection is essential for breeders to

recognize desirable traits and incorporate them into futuregenerations. When the practice

of agriculture began, 8000–10000 years ago, earlier farmersaltered the genetic makeup

by selecting the best performing plants for the nextseason. Originally, the application

of classic genetics principles through visual selection isdefined as conventional plant

breeding. With the development in DNA technologies,molecular tools, such as marker

assisted selection, have been integrated into conventionalbreeding. Later, the basic

process of plant breeding has been challenged by the fastdevelopment of genome

sequencing. In today’s post-genomics era, it is foreseenthat genomic instruments such as

gene editing will revolutionize the plant breedingperformance.

Tomato (Solanum lycopersicum) is a very important vegetablefor both the fresh market

and the processed food industry. The cultivated tomato hasa strikingly narrow genetic

basis because of domestication and true breeding (Bai andLindhout, 2007). In contrast,

tomato’s wild relatives have a wide genetic basis and showremarkable adaptation

to diverse climatic conditions, ranging from very wetrainforests to very dry and arid

conditions (Rick and Chetelat, 1995). Therefore,introgression of alien genes from wild

relatives has played a major role in tomato hybridbreeding, for which molecular tools

have been integrated with traditional breeding method,crossing/backcrossing and

visual selection. In addition, mutagenesis has been appliedto broaden the gene pool.

With the sequences of tomato genomes (Lin et al., 2014),the genetic-based tomato

breeding is being shifted to a DNA-rooted genomic breeding.Considering tomato as an

example, this chapter presents the process of‘conventional’ breeding, which is defined

as an integrated application of classic genetics principlesand genomics through visual

and/or molecular selection. Meanwhile, the potentialapplication of biotechnology tools

in tomato breeding is briefly discussed.

2 Tomato domestication and breeding

2.1 Tomato domestication

Tomato belongs to the genus Solanum of the botanic familySolanaceae. In the Solanum

genus, the section Lycopersicon includes the cultivatedtomato (S. lycopersicum) and

12 additional wild relatives. Tomato is a self-pollinating

diploid species and a model

for genetics. The genome has been sequenced by aninternational consortium (Tomato

Genome Consortium, 2012).

Tomato originated from the Andean region and is most likelydomesticated in Mexico

(Bai and Lindhout, 2007). Domestication refers to theprocess of genetically adapting an

animal or plant to better suit the needs of human beings.Tomato had reached a fairly

advanced stage of domestication before being taken toEurope in the fifteenth century

and further domestication on a much more intense leveloccurred throughout Europe

in the eighteenth and nineteenth centuries. Tomatodomestication has shaped a wide

range of morphological and physiological traits, whichdistinguish the cultivated tomato

from S. lycopersicum cerasiforme, the assumed wild ancestor(Fig. 1). Larger fruit size,

loss of dormancy and higher rate of self-pollination arethe first achievements of tomato

domestication. Several domestication syndrome traits havebeen studied in tomato,

including growth habit (self-pruning, plant height andearliness) and fruit traits (set, size,

shape, colour and morphology). Two genes related todomestication have been cloned

in tomato, fw2.2 and ovate, showing that mutations occurredin them have altered the

function of the wide-type alleles of fruit shape and size(Cong et al., 2002; Tanksley, 2004).

Although domestication occurred in prehistoric times, its

path is being tracked with more

and more available knowledge on genomics (Lin et al., 2014;Blanca et al., 2015). For

example, by extensive resequencing over 500 wild speciesand cultivated varieties of

tomato domestication signatures recorded in the genome arebeing discovered, such as

the two independent sets of quantitative trait loci (QTLs)for large fruit size (Lin et al.,

2014).

2.2 Tomato true breeding

The higher rate of self-pollination that resulted fromdomestication has changed tomato

from partial allogamy to strict autogamy via the transitionfrom exerted to inserted stigmas

(Bai and Lindhout, 2007). Self-pollination results inoffspring nearly identical to the parent,

which contributed greatly to the selection of earliertomato cultivars named heirloom.

A heirloom tomato variety is open-pollinated (pollinationoccurs naturally by insects, birds,

wind etc.) and has a history of being passed down within afamily or community. Heirloom

tomato varieties are unique in size, shape and colour(Watson 1996). At the beginning of

the twentieth century, public institutes (mainly in theUnited States) became more involved

in tomato breeding by applying simple selection methods,which led to true breeding

varieties (Fig. 1). In true breeding plants of a givenpopulation exhibiting desired traits,

such traits can be selected and used for further breedingand cultivation. True breeding

produces homozygous varieties, which in turn produce onlyprogeny identical to the

parent by self-pollination. True breeding occurs mainly byselecting preferred genotypes

in the existing germplasm, which have arisen fromrecombination, natural mutations

and spontaneous outcrossing with wild relatives (Koornneefand Stam, 2001). As the

consequence of inbreeding during tomato domestication andtrue breeding, the genetic

diversity in cultivated tomato is now very narrow.

2.3 Tomato hybrid breeding

In the mid-twentieth century, tomato breeding shifted fromtrue breeding (homozygous

cultivars) to hybrid breeding (heterozygous hybridcultivars). The F 1 hybrid combines good

characters from both parents and outperforms both parentsfor one or more characters

due to heterosis (Semel et al., 2006). The first hybridtomato cultivar ‘Single Cross’ was

Figure 1 The path of tomato domestication and breeding.

released in 1946 (Nederlandse beschrijvende rassenlijstvoor groentegewassen, 1946).

Nowadays, nearly all tomato cultivars for the fresh marketand an increasing number of

cultivars for processing are hybrids.

The art of tomato hybrid breeding is identifying andcombining the specific traits of

two parental breeding lines. Breeders are continuouslyimproving their breeding lines

mainly by two ways. One is to make intra-specific crossesbetween breeding lines which

are either their own lines or from the cultivars of theircompetitors (UPOV breeders rights,

1961). The aim is to generate recombination in asegregating population and to select

progeny plants with favourable traits following a pedigreemethod (Acquaah, 2012). The

other is to make interspecific crosses of the cultivatedtomato with its wild relatives. Then,

new traits from wild germplasm can be introduced into thecultivated tomato through

recurrent backcrossing (Acquaah, 2012). This is theso-called ‘introgression breeding’. An

illustrative example can be found in the industryhighlights box (Introgression breeding on

tomatoes for resistance to powdery mildew) in Chapter 3 ofPrinciples of Plant Genetics

and Breeding (Acquaah, 2012). In earlier generations theparent lines are selected at

a single plant basis. Only when the parental lines are morefixed (F 4 to F 6 ), crosses are

made to produce test hybrids. After several generations oftesting at the breeders’ sites

and eventually at the farmers’ sites, the best hybrids areselected for commercial usage.

Heterosis is only selected for when test hybrids aregenerated (Bai and Lindhout, 2007).

3 Conventional tools in tomato introgression breeding

Wild tomatoes have large genetic diversity, especiallywithin the self-incompatible species

like S. chilense and S. peruvianum (Rick and Chetelat,1995). In 1940, plant breeder Charles

Rick (University of California, Davis) discovered thatcrosses between wild and cultivated

species generated a wide array of genetic variation in theoffspring. Since then, thousands

of accessions of the wild Solanum species have beencollected and maintained at the

Tomato Genetics Resource Center in Davis, California (TGRC,http://tgrc.ucdavis.edu/),

the United States Department of Agriculture (USDA,http://www.ars-grin.gov/npgs/), the

Asian Vegetable Research and Development Center (AVDRC) inTaiwan (http://www.avrdc.

org/germplasm.html) and the Botanical and ExperimentalGarden (http://www.bgard.

science.ru.nl/) in the Netherlands.

Introgression breeding is an important strategy to broadenthe genetic base of highly

inbred crops like tomato, which allows access to all thevariation present in thousands of

Solanum accessions. Introgression of wanted small DNAfragment from donor species

to the crop is often longstanding procedures starting withan interspecific hybridization,

followed by backcrossings with the recipient crop. Aimingat a full utilization of these wild

ancestors as a source of genetic variation, followingconventional and molecular tools

have been integrated to facilitate the transfer of aliengenomic regions containing desired

traits from wild relatives of tomato.

3.1 Overcoming introgressive hybridization barriers

Breeding barriers are sometimes expected in interspecificcrosses, which include unilateral

incompatibility, hybrid inviability, sterility and reduced

recombination. Several tissue

culture techniques, including embryo rescue and bridginglines, have been useful in

overcoming these barriers. Embryo rescue is one of thesuccessful in vitro techniques

for generating viable plants from plant embryos. Embryorescue has been successfully

applied in introgressing resistance traits from S.peruvianum to S. lycopersicum, QTLs for

resistance to bacterial canker (Van Heusden et al., 1999)and the heat-stable resistance to

root-knot nematodes (Cap et al., 1991). In addition toembryo rescue, some wild species,

such as S. pennellii, can serve as a ‘bridge’ to overcomethe unilateral incompatibility and

facilitate introgression breeding (Canady et al., 2006).

3.2 Marker-assisted selection

To introgress the wild favourable allele into cultivatedtomato, marker-assisted selection

(MAS) plays an important role. The mark type hasexperienced transition from morphological

makers, to isozymes considered as the first generation ofmolecular markers, to DNA

based molecular markers such as restriction fragment lengthpolymorphism, amplified

fragment length polymorphism, simple polymerase chainreaction markers in the form

of cleaved amplified polymorphic sequence and sequencecharacterized amplified

region (e.g. Tanksley et al., 1992; Haanstra et al., 1999;Bai et al., 2004). All these marker

information have been made available online(http://sgn.cornell.edu). Breeders use

these markers to a great extent with the main aim toincrease the efficiency of breeding

programmes. With the tomato genome sequences and theresequencing of the wild

relatives (e.g. The 100 Tomato Genome SequencingConsortium, 2014), several single

nucleotide polymorphism (SNP) marker arrays have beendeveloped, including the

SolCAP array produced via the Solanaceae CoordinatedAgricultural Project (SolCAP:

http://solcap. msu. edu/ ;), the one published by Sim etal. (2012) and by Víquez-Zamora et

al. (2013). More information on MAS in tomato breeding canbe found in the chapter of

this book ‘Advances in marker-assisted breeding intomatoes’.

3.3 Exotic introgression line libraries

An introgression line (IL) library consists of a set oflines, each of which carries a single

homozygous chromosome segment from a wild donor species inan elite genetic

background. The individual IL is also recognized as nearlyisogenic lines (also known as

prebreds). In tomato, several IL libraries have beendeveloped for several wild accessions,

for example, ILs of S. pennellii, S. habrochaites, S.lycopersicoides and S. sitiens (http://tgrc.

ucdavis.edu). Each IL population represents a geneticlibrary in which the whole wild

species genome is covered, and has offered tomato breedersa powerful tool to optimize

the uses of the genetic variation in wild relatives. Forexample, the ILs of S. pennellii LA716

in the genetic background of an elite inbred variety M82was made 30 years ago (Eshed

and Zamir, 1995). Using this IL population, alleles thatmaximize tomato yield have been

pyramided and the epistasis among the alleles could bedetected (Gur and Zamir, 2004

and 2015). In addition to ILs, recombinant inbred lines(RILs) derived from interspecific

crosses consist of individuals with mixed parentalchromosome segments. In tomato, RILs

have been made for few wild accessions, for example S.cheesmanii LA483 (Paran et al.,

1997), S. habrochaities LA1777 (Momotaz et al., 2007) andS. pimpinellifolium G1.1554

(Voorrips et al., 2000). These RILs were generated throughsingle seed descent and have

been used for many different experiments to map QTLs forvaluable traits (e.g. Khan et al.,

2012; Víquez-Zamora et al., 2014). In breeding, RILs can bethe starting point for further

development of an IL.

Nowadays, next-generation resequencing approaches have beenapplied in sequencing

the ILs and RILs to define the introgressed chromosomefragments of the donor species.

The SNP information obtained from a marker array and/orgenotype-by-sequencing allows

to detect chromosome regions that are associated withtraits of interest. As an example,

the genotyping of the above-mentioned RIL population of S.pimpinellifolium G1.1554 by

a custom made SNP array and resequencing allowed in silicomapping of tomato yellow

leaf curling virus (TYLCV) resistance derived from S.pimpinellifolium G1.1554 (Víquez

Zamora et al., 2014).

Most of the tomato exotic libraries (Zamir, 2001), such asILs and RILs, were derived from

biparental crosses. In 2014, the first tomato multiparentadvanced generation intercross

(MAGIC) population was generated by intercrossing eighttomato lines derived from

S. lycopersicum and S. lycopersicum cerasiforme (Pascual etal., 2014). The parental lines

of this MAGIC population have been resequenced, which whencoupled with phenotypes

segregating in the population will allow the detection ofcausal QTLs for valuable traits.

With the inspiration of the first intra-specific MAGICpopulation, more inter- and intra

specific MAGIC populations are expected in the near future.

3.4 Chromosomal rearrangements

One of the major problems in introgression breeding iscaused by chromosomal

rearrangements between the donor species and the crop,which has a direct effect on

chromosome pairing at meiosis and hence determines the rateof alien chromatin transfer into

a recipient crop. Since genome structure and genomiccollinearity of the introgression region

between donor species and recipient crops are in most casesunknown, breeders cannot

foresee complications in their introgression breedingprogrammes (Szinay et al., 2010).

Introgression of the tomato Ty-1 gene serves as an

excellent example to illustrate how

the success of introgression breeding can be limited whenchromosomal rearrangements

exist in related species used for interspecific crosses.The Ty-1 gene from S. chilense

LA1969 confers resistance to TYLCV disease. Ty-1 has beenintrogressed into cultivated

tomatoes (Ji et al., 2007). However, the Ty-1 introgressionin these cultivars is generally

accompanied by undesired horticultural traits (such asautonecrosis, http://www.faqs.org/

patents/app/20100212048), a phenomenon that is known as‘linkage drag’. Using tomato

BACs as probes for fluorescent in situ hybridization(FISH), chromosomal rearrangements

were discovered between tomato and S. chilense (Verlaan etal., 2011). Consequently,

recombination was suppressed in the introgressed Ty-1region, resulting in the observed

linkage drag. Moreover, the reduced recombination had ledto an inaccurate map

position of the Ty-1 gene and a wrong breeding approach formore than 15 years. Tomato

chromosome 6 harbours two TYLCV resistance genes, Ty-1assumingly located on the short

arm and Ty-3 mapped on the long arm. Breeders had takeneffects to pyramid them in one

breeding line. In 2013, it was shown that Ty-1 and Ty-3 aredifferent alleles of the same

gene (Verlaan et al., 2013), which had a great impact inrevising breeder’s strategy. Since

Ty-1 and Ty-3 are allelic, one cannot succeed in pyramidingthem into one homozygous

line. Breeders have to combine them in tomato hybridbreeding by introgressing each

allele into one parental line.

Inversions are often observed among tomato and its wildrelatives, which can cause

meiotic pairing disturbances between homoeologues (Szinayet al., 2012). The inverted

region will be genetically inherited as one locus duringthe introgression as crossovers are

unlikely to occur in an inverted region (Szinay et al.,2010). In addition to the Ty-1 example,

more studies have shown that FISH using BAC clones is apowerful tool in the study of

inversions (e.g. Lou et al., 2010; Peters et al., 2012).However, it is difficult to use FISH

when the inversion occurs in a small chromosomal region. Inthe study of the tomato Ty-2

gene conferring TYLCV resistance, resequencing incombination with a de novo genome

assembly has been very helpful to analyse the chromosomalstructure of a wild species

(Wolter et al., 2015).

After the tomato genome, the focus has shifted tosequencing-related wild species

at low read depth to obtain information on sequencevariation by mapping reads to the

reference genome. The assumption is that there is a highdegree of co-linearity within a

species and between closely related species. Resequencingdata consisting of small reads

do not provide positional information of SNP markers, orSNP marker order. Such data

do not uncover the presence of chromosomal rearrangements

in wild species, especially

those that are not closely related to the cultivatedspecies as shown in tomato (Szinay

et al., 2012). Therefore, the occurrence of chromosomalrearrangements stresses the

importance of a de novo genome assembly when wild Solanumspecies are sequenced.

In tomato introgression breeding, both FISH and genomicapproaches can be applied to

visualize chromosomal rearrangements that may hamperintrogressing of a wild allele into

cultivated tomato.

4 Mutagenesis and tomato mutant libraries

Generating genetic variation by mutagenesis treatments hasproven to be a powerful

method for the unravelling of biological processes and thealteration of agronomical

traits in many plant species including tomato (e.g. Mendaet al., 2004; Gady et al., 2009).

Several mutagenesis methods are commonly performed. Theseinclude chemical reagents

such as ethyl methanesulphonate (EMS), physical effectsusing fast neutrons, X- or gamma

rays and insertion of foreign DNA such as transposons andT-DNA. In tomato several

EMS mutation populations have been created in the geneticbackground of cultivated

tomatoes, such as the cultivar M82 (Menda et al., 2004). Alarge tomato mutant collection,

including thousands of mutant phenotypes, has beencatalogued and is searchable at the

Solanaceae Genome Network’s website(http://zamir.sgn.cornell.edu/mutants). Recently,

Micro-Tom is preferred for generating EMS mutantpopulations due to its small size

(10–20 cm height) and short lifecycle (~80 days) (Okabe etal., 2013; Saito et al., 2011;

Shirasawa et al., 2015). Moreover, Micro-Tom is susceptibleto many pathogens that cause

serious problems in tomato production.

Mutants derived from EMS treatments harbour many mutationsat different (random)

locations throughout the genome. The actual number ofaveraged mutations per mutant

is dependent on the amount of mutagen used. In tomato, 1%EMS concentrations are

commonly used for the construction of mutation populations(Menda et al., 2004; Gady

et al., 2009; Minoia et al., 2010). Estimations of themutation frequencies (in 1% EMS

mutation populations) differ, but range between 0.8 and 3.1mutation/Mb (Rigola et al.,

2010; Gady et al., 2009; Minoia et al., 2010). This rangeindicates that in general one

would expect about 10 mutations per chromosomal interval of3 Mb. A map position with

a resolution of 3 Mb would only require a small mappingpopulation (�50 individuals).

4.1 Tomato mutant libraries

To identify valuable traits, a mutation population can bescreened in two ways: forward

and reverse screening. Reverse screening is a targeted waywhen the gene underlying the

trait is known. DNAs of the mutation population can be usedfor targeting-induced local

lesions in genomes (TILLING ) with high-resolution meltingcurve (HRMC) or sequenced

to identify mutation in the wanted gene (Gady et al.,2009). Forward screening can be

done by phenotyping the M2 or M3 families of the mutationpopulation. Once the wanted

mutant(s) is/are identified, mapping/cloning of the casualmutation will be performed.

The most applied way to map a mutation is using a F 2population derived by crossing

Figure 2 Schematic representation of the screening ofavailable EMS-derived M2 mutant families

(~12 plants per family). Mutants (green plants) are beingselected. The selected mutant and the

parental line (can be the background of the mutationpopulation) will be subject to whole-genome

sequencing. Sequencing will result in the identification ofall mutations in the genome of the mutant

(black bars represent the genome of the parental line,white and red stripes, the identified mutations).

All identified mutations will be stored in a database,which will be coupled to a seed stock containing

seed of the sequenced mutants and the parental line. Inaddition, the identified mutation will be

used in the development of HRMC (high-resolution meltingcurve) markers to distinguish mutant from

parental DNA. The M2 family (~150 plants) of thecorresponding mutant can then be used for mapping

the mutation underlying the selected trait (red stripe).

the mutant with a genetically different variety or wildrelative (for increasing of marker

polymorphisms). By screening a large set of F 2 plantswith genome-wide molecular

markers, a first rough map position of the mutation can beobtained. However, the fine

Figure 3 A diagram of mapping/cloning strategy by deepsequencing of bulked segregants in a

segregating population to discover gene of interest (inthis case genes for resistance or susceptibility).

The population can be an M2 family or an F 2 population.For example, a mutant is backcrossed to

its background and F 2 progenies will be tested withpathogens. Resistant and susceptible plants

will be separately pooled and their DNAs will be subject tonext-generation sequencing (e.g. about

20x coverage). The sequence reads will be aligned toreference genome for calling SNPs. Unassociated

mutations will be identified as having a similardistribution in both pools, while the causal mutation

and its genetically linked mutations will be more prevalentin the mutant pool. SNP ratios will be

plotted and mutation locations will be identified as peaks.

mapping of a mutation to a precise chromosomal location isextremely labour intensive

and time consuming for two reasons. The first reason isthat high numbers of plants must

be screened to identify the so-called ‘recombinants’ havinga chromosomal recombination

between markers flanking the mutation. The second reason isthat markers available to

distinguish the DNA from both parents used to generate theF 2 population are usually

limited. The huge amount of work and time (>2 years), whichone has to spend in order to

identify a specific mutation, makes it hardly possible toidentify mutations at a large scale.

Recent advances in sequencing technology have greatlyreduced the time required to

pinpoint induced mutations. Several studies havedemonstrated the power of discovering

mutations via deep sequencing (e.g. Hartwig et al., 2012;Zhu et al., 2012). As illustrated

in Fig. 2, all differences between mutant and itsbackground, including the mutation

underlying the selected trait will be identified bysequencing both the mutant and the

background. Sequences flanking the identified mutations canbe used to design HRMC

markers. A sufficiently large M2 family (100 to 150) can bescreened with the HRMC markers

to pinpoint the mutation underlying the selected phenotype.Alternatively, M2 plants with

contrasting phenotypes, for example resistance andsusceptibility, can be bulked and

sequenced (Fig. 3). Therefore, by a combination ofwhole-genome sequencing of the

mutant and an intelligent use of the corresponding M2families, mutations underlying the

selected phenotypes can be identified rapidly.

Most recently, genome-wide identification of inducedmutations is being performed

in tomato by a whole-genome sequencing analysis (e.g.Shirasawa et al., 2015). As each

mutant is likely to harbour mutations within several genesbesides the one underlying the

selected trait, the sequencing of mutants will result inthe identification of many different

point mutations throughout the genome within each mutant.When all identified SNPs

and phenotypes are put in a database, tomato mutantlibraries are foreseen to play an

important role in reverse genetics studies and in offeringnovel genes/traits to tomato

breeders.

5 Future trends

Novel site-directed mutagenesis techniques have beendeveloped for induction of

targeted small changes in genomes. After the use ofzinc-finger nucleases gene editing

(Lloyd, 2005), other techniques for allele design emerged,such as TALEN-based gene

editing, oligo-directed mutagenesis and CRISPR-Cas9 (seereview of Schaart et al., 2015).

These techniques have been used to make specific smallchanges in genes or promoters,

usually leading to knocking-out of the gene or disruptionof promoter domains. A first

example of this approach refers to the pathogen Xanthomonasoryzae that activates a

susceptibility gene (OsSWEET14) in rice for stimulating therelease of sugars from the

plant cell, thus satisfying the pathogen’s nutritionalneeds. An effector of the pathogen

binds to the promoter and activates OsSWEET14. Li et al.(2012) edited using TALENs the

binding domain in the promoter of OsSWEET14, leading todisease resistance and yet

keeping the developmental function of the gene. In additionto the specificity of these

new site-directed mutagenesis techniques, another advantagecompared to conventional

mutagenesis is their ability to mutate all alleles of the

targeted gene simultaneously, which

is especially beneficial for self-incompatible crops andpolyploid crops. For example, by

combining CRISPR-Cas9 with TALENs, directed mutations ofthe homeoalleles of the MLO

gene have been created in hexaploid wheat (Wang et al.,2014) by editing domains of the

coded protein that are critical for providingsusceptibility.

Such gene-editing techniques in combination with in vitroregeneration, the process of

regenerating whole plants out of plant cells, willrevolutionize plant breeding. For example,

the future success in microspore culture for haploidembryogenesis can facilitate the

application of the double haploid (DH) method in tomatohybrid breeding. DH technology

is a powerful alternative to classic breeding strategiesand has been applied in many crops

of agricultural interest. The extreme recalcitrance oftomato has till now prevented the

application of this technique in tomato breeding. In themodel plant Arabidopsis thaliana,

loss-of-function mutants in CENH3 (Centromic Histone H3)triggers the development of

haploids (Ravi and Chan, 2010). The discovery of the CENH3gene may speed up producing

haploid inducers in tomato by allowing the targetedmanipulation of the tomato CENH3

ortholog. ‘Reverse breeding is a novel plant breedingtechnique designed to directly

produce parental lines for any heterozygous plant, one ofthe most sought after goals in

plant breeding’ (Dirks et al., 2009, p. 837). Reversebreeding can be realized by modifying

genes controlling meiosis. Traditionally, hybrid seeds areproduced by crossing selected

inbred lines. In Arabidopsis, Wijnker et al. (2012) showedthat it is possible to generate

homozygous parental lines from a vigorous hybrid individualby modifying the DMC1

gene. Such a method can be also applied to produce acomplete set of chromosome

substitution lines for a donor plant. Therefore, geneediting may contribute greatly to

the future success of DH techniques and reverse breeding,which will mark the future of

tomato hybrid breeding.


Further information about tomato and its genomics, geneticresources and tools for

breeders can be found at the Solanaceae Genome Network(https://solgenomics.net/).

Regarding breeding tomato, the following books and chaptersare useful:

• Chapter 39 ‘Breeding Tomato’ of the Principles of PlantGenetics and Breeding (Acquaah, 2012).

• ‘Heterosis Breeding in Tomato (Solanum lycopersicum L.):Improvement of Yield and Quality Components’ which iswritten by Yadav and published in 2014 by LAP LambertAcademic Publishing, ISBN-13:978-3-8465-0207-5.

• Genetics, Genomics, and Breeding of Tomato, edited byLiedl, B. E., Labate, J. A., Stommel, J. R., Slade, A. andKole C. and published in 2013 by CRC Press, ISBN9781578088041.

7 Conclusion

Plant breeding is defined as identifying and selecting

desirable traits in plants and

combining these into one individual plant. Since 1900,Mendel’s laws of genetics

provided the scientific basis for plant breeding. Fourconventional breeding methods play

important roles in tomato breeding: (1) true breeding, aprocess also called pure line

selection, occurred in the earlier phase of tomatobreeding; (2) tomato hybrid breeding

to use heterosis, a phenomenon of increased vigour byhybridization of inbred lines; (3)

introgression breeding; and (4) mutagenesis to inducemutations for generating new

genetic variability.

Tomato’s wild relatives have a wide genetic basis and showremarkable adaptation to

diverse climatic conditions, ranging from very wetrainforests to very dry and arid conditions.

Domestication and true breeding has resulted in astrikingly narrow genetic basis of the

cultivated tomato. To compensate such genetic loss,introgression of alien genes from

wild relatives and creation of novel alleles viamutagenesis have played major roles. In

order to enhance the rate of progress of introgressionbreeding, molecular and genomics

tools have been integrated with traditional breedingmethod, crossing/backcrossing and

visual selection (Fig. 1).

The ‘conventional’ breeding cycle is being challenged bythe combination of advances

in next-generation sequencing and gene editing, which arediscussed in the following

chapters in this book.

8 Acknowledgements

I thank Dr Robin P. Huibers and Dr Henk Schouten for theircontribution to Fig. 2 and 3,

respectively.

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9 Chapter 9 Advances in marker-assistedbreeding of tomatoes

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10 Chapter 10 Genetic engineering oftomato to improve nutritional quality,resistance to abiotic and bioticstresses, and for non-food applications

1 Introduction

Genetic engineering is among the fastest adopted croptechnologies in modern history

with global hectarage increasing from 1.7 million in 1996to 179.7 million in 2015 (James,

2015, ISAAA). Successful transformation of plant cellsstarted with genes of bacterial origin

(in 1983) involving academicians in the United States andEurope as well as biotechnology

companies, including Monsanto (Bevan et al., 1983; Fraleyet al., 1983; Hererra-Estrella

et al., 1983; Murai et al., 1983). The first geneticallyengineered food with superior shelf life

trait released in the market was the Flavr Savr tomato in1994 (Kramer and Redenbaugh,

1994; Kramer et al., 1990, 1992). The standardizedtransformation protocols and ease

of tissue culture for tomato led to genetic engineering forspecialized traits and process

development of a great number of new lines evidenced by 786instances of notifications

and permits for field trials between 1986 and 2016(Virginia Tech University, 2016,

Information Systems for Biotechnology).

Tomato (Solanum lycopersicum L.) has thus become anexcellent research model for

elucidation of fundamental physiological processes,molecular genetics, development and

pathology in general, and fruit development and ripeningstudies in climacteric fruits in

particular (Meissner et al., 1997; Fatima et al., 2008;Klee and Giovannoni, 2011; Upadhyay

et al., 2013, 2014; Anwar et al., 2015). The deciphering ofthe genome of inbred tomato

cultivar, Heinz 1706 (Sato et al., 2012, The Tomato GenomeConsortium) and multitude

of genetic resources together with established regulatoryframework well in place have

made tomato a model fruit for genetic dissection. Inaddition, fruit ripening mutants

(Giovannoni, 2004, 2007) and genetic linkages for fruitquality have culminated into a

very clear road map for scientists to further unravel theintricacies of genes governing

fruit quality attributes as well as fundamental metabolicprocesses. The relatively small

(950 Mb) tomato genome is organized into 12 chromosomescomprising 34 727 genes

that encode proteins, of which 30 855 genes aresupported/validated by RNA sequencing

data (Sato et al., 2012).

A member of the Solanaceae family which contains more than3000 species, including

equally and economically important crops such as potato,eggplant, tobacco, petunia

and pepper (Bai and Lindhout, 2007), tomato is the secondmost consumed vegetable

next to potato (FAOSTAT, 2015). Mainland China led theaverage yearly global

production of tomatoes from 1961 to 2014 at 14.6 MillionTonnes (MT) followed by the

United States at an average yearly production of 9.2 MT(FAOSTAT, 2015). Fresh and

processed tomatoes account for returns of more than $2billion annually in the United

States (Economic Research Service, USDA, 2016). In light ofthe potential anti-cancer

and anti-oxidative properties of lycopene, ß-carotene andflavonoids, and phytonutrients

abundant in tomato, the production and consumption oftomato are projected to rise

every year (Raiola et al., 2014). A high global demand fortomatoes, particularly in the

processing industry, requires improvements in economicallyimportant agronomic traits

(Fatima et al., 2013).

High-efficiency transformation and a reproducibleregeneration protocol are central to

functional genomics studies with this important vegetablecrop. Synthetic biology has given

impetus to engineering genes for introduction of new traitsand biochemical pathways

into crop plants of interest (Lu et al., 2013). Inaddition, co-introduction or pyramiding of

multiple genes into vector constructs for transformationhas been demonstrated to be

efficacious for engineering metabolic pathways andresistance against pathogens in plants

(Ye et al., 2000; Zhao et al., 2003; Abdeen et al., 2005).

This chapter provides comprehensive information on geneticengineering studies

that have introduced beneficial traits in tomato. The vastbibliographic database was

made possible to view through Scopus and Purdue Universitylibrary (www.lib.purdue.

edu), to sift through literature from 1983 to 2016. Usingkeywords such as tomato,

genetic engineering, transformation,Agrobacterium-mediated, fruit quality, biotic stress

tolerance, abiotic stress tolerance, salinity and manyothers resulted in the listing of

hundreds of relevant publications. However, not alldocuments listed dealt with genetic

engineering studies. Many reviews on genetic engineeringand tomato serve as valuable

resource in refining this chapter (Razdan and Mattoo, 2006;Fatima et al., 2008; Handa

et al., 2010, 2012; Pandey et al., 2011; Khaliluev andShpakovskii, 2013; Bergougnoux,

2014; Nath et al., 2014). Herein we focus on tomatotransformed for introduction

and manipulation of transgenes for four broad categories:improved fruit quality and

enhancement of shelf life, abiotic stress tolerance, bioticstress tolerance and production

of oral vaccines.

2 History of tomato transformation and challenges

Attempts to modify tomato started with egg transformationusing irradiated pollen

but failed (Sanford et al., 1984). Soon thereafter, thefirst success that heralded genetic

transformation of tomato involved Agrobacterium tumefaciensas the carrier and tomato

leaf disks (McCormick et al., 1986). Various explants suchas cotyledons (Abu-El-Heba

et al., 2008; Kaur and Bansal, 2010), epicotyls, hypocotyls(Moghaieb et al., 2004), stems

(Ma et al., 2015), petioles (Sigareva et al., 2004),

internodes (Chyi and Phillips, 1987) and

leaves (Agharbaoui et al., 1995) have been used ever sinceto develop transformation and

regeneration methods for different tomato cultivars.Factors that need to be considered

while embarking on tomato transformation include age of theexplant (Davis et al., 1991),

type of the explant (Sigareva et al., 2004; Hasan et al.,2008), size of the explant (Chaudry

et al., 2010; Ajenifujah-Solebo et al., 2012) and thecultivar to be used (Ellul et al., 2003;

Cortina and Culianez-Macia, 2004; Ume-e-Ammara et al.,2014). In addition, other factors

such as using nurse cells or feeder layers, complex mediacombinations (Wu et al., 2011a),

subculture frequency, adding plant growth regulators(Ume-e-Ammara et al., 2014),

inclusion of acetosyringone, type and concentration ofantibiotics as marker, co-cultivation

time and plasmid vector construction (Yasmeen et al., 2009)are variables that can impact

the establishment of a robust and reliable transformationregimen for tomato. Higher

shoot organogenesis was obtained from hypocotyl explantsrather than cotyledons from

three tomato varieties and the addition of thidiazuronenhanced their shoot differentiation

(Murlidhar Rao et al., 2007).

Efficient transformation methods have been reported fordefensin gene (El-Siddig et al.,

2011) and coat protein of tomato yellow leaf curl virususing different media formulations that

particularly included growth regulators such as putrescine,

zeatin riboside and indole acetic

acid (Ume-e-Ammara et al., 2014). An efficientAgrobacterium-mediated transformation

protocol on tomato cotyledons enabled studies on the effectof different variables such

as seed germination medium, seedling age, pre-cultureduration, co-cultivation medium,

pH of medium, kanamycin concentration and tobacco feedercell layer on transforming

three tomato cultivars (Rai et al., 2012). Thus,pre-culturing the explant for 6 days after

a 5-min inoculation with Agrobacterium culture in MS mediumfortified with 8.9 mM

6-benzyladenine, 9.3 mM kinetin and 0.4 mgL −1 thiamine,pH 5.0, was beneficial for obtaining

high transformation frequency with a number of tomatocultivars (Rai et al., 2012). Notably,

the layering of tobacco feeder cell contributed little tothe transformation efficiency of the

few tomato cultivars studied.

Effects of stage of explants (stem from 4–5-day-oldseedling and cotyledon from

8–9-day-old seedling), pre-culture duration (3 days forstem and 2 days for cotyledon),

Agrobacterium density (OD 600 = 0.6 for both explants),infection time (15 min for stem and

20 min for cotyledon) and co-cultivation duration (4 daysfor stem and 3 days for cotyledon)

were analysed to develop a high-throughput transformationprotocol for transformation of

Crocus sativus zeaxanthin 7,8-cleavage dioxygenase gene intwo Chinese tomato cultivars,

Zheza No.905 and Shengya (Ma et al., 2015). Transformation

efficiency of cotyledon and

stem explants was 26.33% and 28.00% for Zheza No.905 and19.33% and 23.33% for

Shengya, respectively.

3 Genetic engineering of tomato for fruit quality andshelf life

Fruits, derived from different parts of a flower, arehighly diverse in their structure and

physiological functions (Handa et al., 2012). Fruit qualityattributes such as long post

harvest shelf life, attractive colour, large size, highnutritive value, improved palatability

and optimum rheological properties for processing areeconomically advantageous for

farmers and supply chain personnel alike with a value forthe money of the consumers.

The maiden genetically engineered tomato, Flavr Savr(CGN-89564), with reduced

polygalacturonase (PG) expression via antisense RNAtechnology (later found to be

mediated by interfering RNAs, Krieger et al., 2008),enabled superior juice viscosity and

shelf life, and was commercialized over 20 years ago(Kramer and Redenbaugh, 1994;

Kramer et al., 1990, 1992). It paved the way forexperimentalists and researchers to tap

into numerous genes governing tomato fruit qualityattributes for use in the genetic

manipulation to develop better quality tomatoes in terms ofshape, size, texture,

phytonutrient levels and volatiles (selected examples inTable 1).

Fruit architecture, size and shape in tomato are inherited

by cumulative gene action.

Fruit shape variation has been attributed to mutationsfound in one of the following four

genes, SUN, OVATE, LOCULE NUMBER (lc) and FASCIATED (fas)(Rodriguez et al., 2011).

The former two genes regulate fruit elongation while thelatter ones govern locule number

and flatness of fruit. Overexpression of SUN driven by CaMV35S (Cauliflower mosaic

virus 35S) promoter led to the development of aparthenocarpic elongated fruit due to

changes in cell division pattern (Wu et al., 2011b). Thesefruit had increased cell number

longitudinally and decreased in those in the transversedirection in the developing fruit. SUN

expression was hypothesized to perturb auxin levels butthis remains to be demonstrated.

Overexpression of IQD12 (a protein containing an IQ67domain consisting of multiple

IQxxxRGxxxR motifs) at the SUN locus increased fruitelongation, while silencing it by RNAi

decreased fruit elongation (Xiao et al., 2008). OVATE is arepressor of transcription and leads

to reduced fruit size; however, it determines fruit shapepattern prior to anthesis (Bohner

and Bangerth, 1988; Liu et al., 2002; Monforte et al.,2014). Overexpression of OFP1 or

ectopic overexpression of OVATE under the control of CaMV35S promoter reduced

fruit elongation in tomato (Ku et al., 1999) or producedround fruit (Liu et al., 2002). FAS,

expressed early during the development of stamens andcarpels, is a transcription factor

belonging to the YABBY family of genes (involved in leaf,flower and fruit development),

nine of which have been characterized in tomato both insilico and experimentally (Han et

al., 2015). FAS and lc exhibit an epistatic interactionwith fas having a stronger effect by

increasing the locules’ number from 2 to 6 while lcincreases the number to 3 or 4 (Lippman

and Tanksley, 2001). Two SNPs located in lc locus wereattributed with function to increase

locule number (Muños et al., 2011). Map-based cloningplaced the two SNPs downstream

of WUS (WUSCHEL, homeobox transcription factor) gene(required for shoot and floral

integrity). The final fruit size is determined by cellexpansion via endoreduplication, a form

of nuclear polyploidization (Cheniclet et al., 2005), whichis induced by cyclin-dependent

kinase inhibitors such as WEE1 (Sun et al., 1999). Ploidylevels along with fruit mass, growth

Table 1 Genetic engineering of tomato for improved/alteredfruit quality

d-galacturonate

reductase FaGalUR

Fragaria x ananassa

(strawberry) Ectopic expression of FaGalUR gene driven byconstitutive CaMV 35S (Cauliflower mosaic virus 35Spromoter) and fruit-specific polygalacturonase promoterIncreased vitamin C content and antioxidant capacityAmaya et al., 2015

Homogentisate

phytyltransferase (HPT),

tocopherol cyclase

(TCY) and g-tocopherol

methyltransferase (TMT)

Synechocystis sp.

(cyanobacteria) Plastid genome engineering by assembly ofmonocistronic expression cassettes for HPT, TCY and TMTin plastid expression vector pHK20 Expression oftocochromanol biosynthesis in chloroplasts andchromoplasts for high vitamin E activity in tomato Lu etal., 2013

Lycopene b-cyclase

(Lycb-1) (Citrus) Overexpression of Lcyb-1 driven by CaMV35S Fourfold increase in b-carotene and increased totalcarotenoids Guo et al., 2012

9-cis-Epoxycarotenoid

dioxygenase 3 (NCED1)

Solanum lycopersicum Fruit-specific silencing (E8) ofSlNCED1 by RNAi Increased accumulation of b-carotene andlycopene, decrease in abscisic acid Sun et al., 2012

Spermidine synthase

(MdSPDS1)

Malus x domestica

(apple) Overexpression of MdSPDS1 driven by CaMV 35SIncreased lycopene content Neily et al., 2011

TOMATO AGAMOUS

LIKE 1

TAGL1 (S. lycopersicum) Overexpression of (TAGL1-SRDX)under fruit ripening-specific tomato E8 promoter Decreasein lycopene and isoprenoids Itkin et al., 2009

TAGL1

S. lycopersicum Overexpression of TAGL1 driven by CaMV35S Increase in lycopene and naringenin chalcone Itkin etal., 2009

UV-DAMAGED DNA

BINDING PROTEIN 1

DDB1

S. lycopersicum Fruit-specific RNAimediated repression ofDDB1 driven by E8 promoter Increased pigment accumulationby virtue of increased plastid compartment space Wang etal., 2008 (Continued)

Table 1 (Continued)

Geraniol synthase

GES

Ocimum basilicum Overexpression of GES under fruitripeningspecific tomato polygalacturonase promoterIncrease in carotenoidderived aroma volatiles but decreasein carotenoids like phytoene, lycopene and b-caroteneDavidovich-Rikanati et al., 2007

Phytoene synthase

SlPsy-1

S. lycopersicum Overexpression of Psy-1 driven by CaMV35S 1.2-fold increase in total carotenoids, 1.3-foldincrease in b-carotene, 2.3-fold increase in phytoene,1.8 fold increase in phytofluene, decrease inphenylpropanoids and flavonoids Fraser et al., 2007

Lycopene b-cyclase

crtY Erwinia herbicola

or carRA Phycomyces

blakesleeanus Overexpression of crtY or carRA driven byatpI (ATPase IV subunit) tobacco plastidspecific promoterFourfold increase in b-carotene accumulation, slightdecrease in lycopene and total carotenoids Wurbs et al.,2007

Fibrillin

FIB1, FIB2

Capsicum annuum Overexpression of capsicum fibrillingenes driven by their own promoter Twofold increase incarotenoids, for example 118% increase in lycopene, 64%increase in b-carotene, 36% increase in b-ionone, 74%increase in b-cyclocitral, 50% increase in citral, 122%increase in 6-methyl5-hepten-2-one and 223% increase ingeranylacetone Simkin et al., 2007

1-Deoxy-d-xyluose-5

phosphate synthase

DXS

Escherichia coli Expression of DXS driven by CaMV 35S orfibrillin promoter 1.6-fold increase in total carotenoids,2.4-fold and 2.2-fold increase in phytoene andb-carotene, respectively Enfissi et al., 2005

Cryptochrome 2

CRY2

S. lycopersicum Overexpression of CRY2 driven by CaMV 35S1.5-fold increase in lutein, 1.7-fold increase in totalcarotenoids and 2.9-fold increase in flavonoidsaccumulation Giliberto et al., 2005

Table 1 (Continued)

DE-ETIOLATED 1

DET1

S. lycopersicum Fruit-specific RNAimediated inhibition ofDET1 driven by P119, 2A11 and TFM7 promoters Twofoldincrease in lycopene, fourfold increase in b-caroteneand 3.5-fold increase in flavonoids Davuluri et al., 2005

Lycopene b-cyclase

Lyc-b

S. lycopersicum Overexpression of Lyc-b driven by CaMV35S 31.7-fold increase in b-carotene D’Ambrosio et al.,2004

ELONGATED

HYPOCOTYL 5

HY5

S. lycopersicum RNAi-mediated repression of HY5 driven byCaMV 35S Decrease in total carotenoids Liu et al., 2004

CONSTITUTIVELY

PHOTOMORPHOGENIC

1

COP1-like

S. lycopersicum RNAi-mediated repression of COP1likedriven by CaMV 35S Twofold increase in total carotenoidsLiu et al., 2004

Lycopene b-cyclase

b-Lcy Arabidopsis

thaliana

carotene b-hydroxylase

b-Chy

C. annuum Overexpression of bLcy and b-Chy genes drivenby tomato phytoene desaturase promoter 12-fold increasein b-carotene and 10-fold increase in total xanthophyllDharmapuri et al., 2002

Phytoene synthase

CrtB

Erwinia uredovora Fruit-specific expression driven bypolygalacturonase promoter 2.4-fold increase in phytoene,1.8-fold increase in lycopene and 2.2-fold increase inb-carotene Fraser et al., 2002

SAM decarboxylase SPE2

Saccharomyces

cerevisiae Overexpression of SPE2 driven by fruitspecificE8 promoter Two–threefold increase in lycopene, increasein transcripts related to flavonoid biosynthesis genesMehta et al., 2002; Mattoo et al., 2007

Phytoene desaturase CrtI

E. uredovora Overexpression of Crtl driven by CaMV 35SThreefold increase in b-carotene but decrease in lycopeneand phytoene Römer et al., 2000

Lycopene b-cyclase SpB

S. pennellii Overexpression of SpB driven by CaMV 35SGreater than sixfold increase in b-carotene but 1.8-folddecrease in lycopene Ronen et al., 2000 (Continued)

Table 1 (Continued)

SpB

S. pennellii Antisense-mediated downregulation of SpBdriven by CaMV 35S Greater than sixfold decrease inb-carotene and a slight increase in lycopene Ronen etal., 2000

b-Lcy

A. thaliana Overexpression of b-Lcy gene driven by tomatophytoene desaturase promoter Greater than sixfoldincrease in b-carotene Rosati et al., 2000

b-Lcy

S. lycopersicum Antisense-mediated downregulation of bLcydriven by tomato phytoene desaturase promoter 1.3-foldincrease in lycopene; 1.7-fold increase in lutein; 50%decrease in b-Lcy expression Rosati et al., 2000

SlPsy-1

S. lycopersicum Overexpression of Psy-1 driven by CaMV35S High lycopene content accompanied by decrease inplant height and 30-fold decrease in gibberellin GA 1Fray et al., 1995

Pectin methylesterase

PME

S. lycopersicum Antisense-mediated downregulation of PMEdriven by CaMV 35S Increased juice and serum viscosity,higher precipitate weight ratio, increased size anddegree of pectin methoxylation Tieman et al., 1992;

Thakur et al., 1996a, 1996b

Lipoxygenase B

LoxB

S. lycopersicum Cosuppression under CaMV 35S Impaired MeJAproduction, altered metabolome and aminome Kausch et al.,2012

viscosity 1

vis1

S. lycopersicum Silencing of vis1 gene by RNAi technologyEnhanced ripening qualities under heat stress Metwali etal., 2015

Spermidine synthase

SPE3

S. cerevisiae Overexpression of SPE3 driven by CaMV 35SFruit shelf life, shrivelling and delayed decay,increased lycopene content Nambeesan et al., 2010

Anthocyanin1

ANT1

S. chilense Overexpression of ANT1 driven by CaMV 35SIncreased anthocyanadins (petunidin, malvidin,delphinidin) in fruit Schreiber et al., 2012

Table 1 (Continued)

Delila

Del

Antirrhinum majus Overexpression of Del driven by CaMV 35S23-fold increase in anthocyanins in mature leaves alongwith 40-fold and 50-fold increase in corolla and stamen,respectively, no change in fruit Mooney et al., 1995

RP

Myc-rp

Perilla fructescens Overexpression of RP driven by CaMV

35S Increase in anthocyanins in vegetative tissues andflowers Gong et al., 1999

LC, a member of maize R

gene family of MYC-type

transcription factors

Zea mays Overexpression of LC driven by CaMV 35S Increasein anthocyanins in all vegetative tissues Goldsbrough etal., 1996

Chalcone isomerase

Chi-A

Petunia hybrida Overexpression of Chi-A driven by CaMVdouble35S 78-fold increase in peel flavonols accumulationprimarily rutin Muir et al., 2001

Transcription factors

C1 (MYB-type) and LC

(MYC-type)

Z. mays Overexpression of C1 and LC driven byfruitspecific E8 or CaMV double35S Induced flavonoidsynthesis in fruit flesh with a 10-fold increase in totalflavonoids and 20-fold increase in total flavonols,primarily kaempferol Bovy et al., 2002

ANT1

S. lycopersicum Overexpression of SlANT1 driven by CVM(Cassava vein mosaic promoter) 500-fold increase inanthocyanin accumulation Mathews et al., 2003

Chalcone synthase Chs1

S. lycopersicum RNAi-mediated repression of Chs1 drivenby CaMV d35S Decrease in total flavonoids, parthenocarpicfruit Schijlen et al., 2007

Stilbene synthase

StSy

Vitis vinifera (grapes) Overexpression of StSy driven by

CaMV 35S Increased accumulation stilbenes (resveratroland piceid) and naringenin chalcone, rutin Schijlen etal., 2006

Chalcone synthase (Chs1)

P. hybrida

Chalcone reductase

(CHR) Medicago sativa Overexpression of Chs1 and CHRdriven by CaMV 35S Increase in butein andisoliquiritigenin accumulation along with naringeninchalcone and rutin Schijlen et al., 2006 (Continued)

Table 1 (Continued)

Chalcone isomerase

(CHI)

P. hybrida

Flavone synthase

(CYP93B2) Gerbera

hybrida Overexpression of CHI and CYP93B2 driven by CaMV35S 16-fold increase in rutinflavonol, increasedaccumulation of luteolin-7-glucoside, luteolinaglycon,quercetin glycosides, naringenin chalcone and rutinSchijlen et al., 2006

Stilbene synthase (StSy)

V. vinifera Overexpression of StSy driven by CaMV 35SIncrease in transresveratrol (48.48 mg kg −1 freshweight), trans-piceid (126.58 mg kg −1 fresh weight),twofold decrease in rutin, 2.4-fold decrease innaringenin, seedless fruit Giovinazzo et al., 2005;Nicoletti et al.,2007

Cullin 4 (CUL4)

S. lycopersicum RNAi-mediated repression of CUL4 drivenby CaMV 35S Increase in anthocyanins accumulation andcarotenoids (twofold increase in lycopene) Wang et al.,2008

Isoflavone synthase (IFS2)

Glycine max Overexpression of IFS2 driven by CaMV 35SIncreased accumulation of genistin in leaves andnaringenin chalcone in fruit peel Shih et al., 2008

Rosea1 and Delila

A. majus Overexpression of AmRos1 and Del under fruitripeningspecific tomato E8 promoter Increase in pericarpanthocyanins comparable to blueberries and blackberriesButelli et al., 2008

MYB12

S. lycopersicum Silencing of SlMYB12 driven by CaMV 35Sby RNAi technology Decrease in flavonoid pigmentnaringenin chalcone, y-like phenotype Adato et al., 2009

MYB12

S. lycopersicum Overexpression of SlMYB12 driven by CaMV35S Rescued colourless peel, y tomato mutant phenotypeAdato et al., 2009

Stilbene synthase

StSy

V. vinifera Overexpression of grape StSy under control offruit-specific promoter TomLoxB Increased accumulation ofresveratrol, transresveratrol and piceid D’Introno et al.,2009

w-3 fatty acid desaturase

FAD3Brassica napus or/

and FAD7

S. tuberosum Overexpression of FAD3 and FAD7 driven byCaMV 35S Increase in C18 polyunsaturated fatty acidsDomínguez et al., 2010

Table 1 (Continued)

3-Hydroxy-3-methyl

glutaryl CoA reductase

HMGR-1

A. thaliana Overexpression of HMGR-1 driven by CaMV 35S2.4-fold increase in total phytosterol Enfissi et al.,2005

Salicylic acid

methyltransferase SAMT

S. lycopersicum Overexpression of SAMT driven by FMV 35S(Figwort mosaic virus) 123-fold increase in methylsalicylate Tieman et al., 2010

MYB12

A. thaliana Overexpression of AtMYB12 driven by CaMV 35S27-fold increase in chlorogenic acid, 26-fold increase indicaffeoylquinic acid, 42-fold increase intricaffeoylquinic acid, 67-fold increase inquercetinrutinoside, 593-fold increase inkaempferolrutinoside Luo et al., 2008

Amino acid aromatic

decarboxylase (AADC1A)

S. lycopersicum Overexpression of AADC1A driven by FMV35S 10-fold increase in 1-nitro-2phenylethane,2-phenylethanol and 2-phenylacetaldehyde Tieman et al.,2006

Odorant 1

ODO1

P. hybrida Overexpression of ODO1 driven by fruitspecificE8 promoter No increase in phenylalanine-derived volatilecompounds Dal Cin et al., 2011

S-linalool synthase

LIS

Clarkia breweri Overexpression of LIS driven byfruit-specific E8 promoter Increase in S-linalool and8-hydroxylinalool Lewinsohn et al., 2001

a-Zingiberene synthase

ZIS

O. basilicum Overexpression of ZIS under fruitripeningspecific tomato polygalacturonase promoterAccumulation of high levels of a-zingiberene (224-1000 ngg −1 fresh weight) and other sesquiterpenesDavidovich-Rikanati et al., 2008

Carotenoid cleavage

dioxygenase CCDIBS.

lycopersicum Antisense-mediated downregulation of CCDIBdriven by FMV 35S 50% decrease in b-ionone, greater than60% decrease in geranylacetone but no morphologicalalterations or changes in carotenoids Simkin et al., 2004

Lipoxygenase

TomLoxC S. lycopersicum Antisense-mediated downregulationof TomLoxC driven by CaMV 35S 1.5% decrease in hexanal,hexenal and hexanol Chen et al., 2004

and seed size were reduced in tomato upon silencing WEE1under the control of CaMV 35S

by antisense technology (Gonzalez et al., 2007). A cellcycle switch, CCS52A, arrests cell

division and promotes endoreduplication (Cebolla et al.,1999). Overexpression of CCS52A

activated anaphase-promoting complex E3 ubiquitin ligaseand led to increased tomato

fruit size (Mathieu-Rivet et al., 2010).

Taste, flavour and texture are important fruit qualityattributes and important candidates

for modification. Taste of tomato fruit may vary from beingsweet to acidic as a result of a

delicate balance between sugars and organic acids.Thaumatin, a sweet-tasting protein,

is produced by an African plant, Thaumatococcus danielliiBenth (Van der Wel and Loeve,

1972). Engineering of thaumatin gene in tomato producedfruits with an enhanced sweet

taste and particularly a sweet-based aftertaste(Bartoszewski et al., 2003). Overexpression

of a-zingiberene synthase and geraniol synthase genes fromOcimum basilicum driven

by ripening-specific PG promoter resulted in tomatoesaccumulating geraniol, an acyclic

monoterpene (Davidovich-Rikanati et al., 2007, 2008). Thesefruits had a floral aroma

but were deficient in nutrient content, including reducedcarotenoid levels. Fruit-specific

expression of yeast S-adenosylmethionine decarboxylase(ySAMdc) enabled ripening

specific accumulation of polyamines, spermidine andspermine; longer vine life; and

higher levels of lycopene in tomato fruit (Mehta et al.,2002). These fruit had enhanced

accumulation of glutamine, asparagine and organic acids inthe red fruit with significant

decreases in the contents of valine, aspartate, sucrose andglucose. Notably, these fruit

were found to have an increased acid to sugar ratio, anattribute desired by geneticists for

providing enhanced flavour and aftertaste to tomato (Mattooet al., 2006, 2007).

Ethylene is a gaseous plant hormone pivotal to climactericfruit ripening and softening

(Oeller et al., 1991; Mattoo and Suttle, 1991; Fluhr andMattoo, 1996). Biochemical

pathways involving its biosynthesis, degradation andperception have been common

engineering targets for enhanced shelf life and freshnessof climacteric fruits (Klee and

Giovannoni, 2011). Suppression of biosynthesis genes in the

ethylene pathway such as

aminocyclopropane-1-carboxylic acid (ACC) synthase (Oelleret al., 1991) or ACC oxidase

(Hamilton et al., 1990) became a favoured strategy forresearchers. ACC, the critical

intermediate in ethylene biosynthesis was also madelimiting by respective overexpression

of S-adenosyl methionine hydrolase (Good et al., 1994) orACC deaminase (Klee et al.,

1991). Cell wall architecture, a major determinant of fruittexture, is governed by more than

50 genes (Sato et al., 2012; The Tomato Genome Consortium,2012). Lowered ethylene

delays fruit softening, characteristic of ripening, byhindering textural changes induced

by cell wall degradation enzymes such as pectinmethylesterase (PME) and PG. PG was

downregulated by constitutive expression of chimericanti-PG in tomato cultivar Ailsa Craig

(Smith et al., 1990). Transgenic line homozygous foranti-PG in the T2 generation had 99%

reduction in PG activity and concomitant decrease in pectindepolymerization. Ethylene

and lycopene accumulation were not affected by anti-PGexpression. PME, believed to

have a role in determining fruit texture, was alsodownregulated by anti-PME3 driven

by CaMV 35S promoter in tomato. No effect on fruitsoftening was observed in these

fruits, but fortuitously juice viscosity and total solublesolids were enhanced (Tieman et al.,

1992; Tieman and Handa, 1994; Thakur et al., 1996a,b).Suppression of ripening-specific

N-glycoprotein modifying enzymes, a-mannosidase andb-d-N-acetylhexosaminidase, led

to firmer fruits relative to controls and enhanced shelflife of tomatoes (Meli et al., 2010).

Chlorophyll degradation and accumulation of carotenoids arehallmarks of ripening

tomato (Alexander and Grierson, 2002). Phytoene synthase(Psy) catalyses the first step in

carotenoid biosynthesis pathway, the condensation of twomolecules of geranyl geranyl

diphosphate (GGPP) into phytoene. Overexpression of Psy1gene driven by CaMV

35S promoter in tomato resulted in high lycopene contentbut with dwarf plants that

exhibited 30-fold decrease in gibberellin GA 1 (Fray etal., 1995). It was postulated that

lycopene synthesis occurred at the expense of gibberellinsby diverting the common

GGPP precursor to carotenoid pathway because of theconstitutive Psy1 overexpression

in the transgenic tomato. Mitigation of the dwarfingphenotype was achieved when fruit

specific PG promoter was used to drive the expression ofcrtB (Psy from Erwinia uredovora)

(Fraser et al., 2002). The bacterial gene was fused withtomato Psy1 transit sequence

for chromoplast targeting. Suppression by RNAi of DET1(DEETIOLATED 1), a negative

regulator of photomorphogenesis, increased the content ofboth carotenoids and

flavonoids with no negative effects on the plant phenotypeof the transgenic tomatoes

(Davuluri et al., 2005).

Flavonoids are polyphenolic hydrophilic, aromatic smallmolecules synthesized via the

phenylpropanoid pathway (Ververidis et al., 2007).Malonyl-CoA and p-coumaroyl-CoA,

derived from carbohydrate metabolism and phenylpropanoidpathway, respectively,

are the reactant molecules for most flavonoids (Forkmannand Heller, 1999). These

compounds, abundant in fruit cuticles (Hunt and Baker,1980), contribute to fruit colour,

flavour and texture. Tomato pericarp is deficient inflavonoids due to low or no expression

of the biosynthesis genes (Bovy et al., 2007). Metabolicengineering strategies for

flavonoid compounds in tomato include (i) overexpression ofstructural and regulatory

heterologous genes of flavonoid pathway, (ii) RNAinterference for blocking steps/branches

of the pathway and (iii) introducing novel pathway branchesfor new flavonoids (Bovy et

al., 2007). A four-gene construct containing Petuniachalcone synthase (CHS), chalcone

isomerase (CHI), flavanone-3-hydroxylase (F3H) and flavonolsynthase (FLS) was used in

an attempt to upregulate levels of flavonols in fleshytomato fruit (Colliver et al., 2002).

Orchestrated action of all four genes led to increasedlevels of flavonols in both peel

(quercetin glycosides) and flesh (kaempferol glycosides).Fruit-specific expression using

the E8 promoter in front of two transcription factors,Rosea1 (Ros1) and Delila (Del), which

are activators of anthocyanin biosynthesis enhancedanthocyanin production in tomato

pericarp at concentrations comparable to that inblackberries and blueberries (Butelli et

al., 2008). Identification and quantification of sevenanthocyanins by LC-MS/MS including

two novel anthocyanins,malvidin-3-(p-coumaroyl)-rutinoside-5-glucoside andmalvidin-3

(feruloyl)-rutinoside-5-glucoside, was carried out intransgenic purple tomatoes expressing

transcription factors, Del and Ros1 (Su et al., 2016).

RNA interference-mediated silencing of tomato CHS1 led to asignificant reduction

(99% reduction of total flavonoids) of naringenin chalconeand quercetin rutinoside

in comparison with wild-type controls (Schijlen et al.,2007). Such silenced tomato

fruits had abnormal phenotype and showed parthenocarpicfruit development.

Similarly, seedless fruits or ones with reduced seed setwere obtained when grape

stilbene synthase was expressed (Giovinazzo et al., 2005;Schijlen et al., 2006) in

tomato. These observations indicated an important role offlavonoids in fertilization,

seed and fruit development. Fruit-specific expression ofthe Arabidopsis MYB12

transcription factor in tomato led to production of novelbioactive flavonoids,

particularly flavonols and caffeoyl quinic acids (Zhang etal., 2015). ChIP-qPCR

(chromatin immunoprecipitation-quantitative PCR) assaysshowed that AtMYB12

bound directly to promoters of genes involved in both

primary and secondary

metabolism. Co-expression of feedback-insensitiveEscherichia coli 3-deoxy-d

arabinoheptulosonate 7-phosphate synthase (AroG) andpetunia MYB transcript

factor, ODORANT1 (ODO1), in tomato fruits led to a dualeffect on phenylalanine

and related biosynthetic pathways (Xie et al., 2016).Positive impact was seen on

the content of tyrosine and metabolites derived fromcoumaric and ferulic acids

but secondary metabolites downstream the phenylalaninepathway, including

kaempferol, naringenin and quercitin-derived metabolites,as well as aromatic

volatiles were negatively impacted.

4 Abiotic stress tolerance

Plants have developed very sophisticated molecularmechanisms to evade stress situations,

likely because of being sessile. Environmental extremestherefore impact plant growth and

development on a daily basis, and in wake of the currentglobal climate change additional

unfavourable effects on plant yield is furthered by abioticstresses including salinity,

drought, high light, flooding, wounding, cold and heat(Ainsworth and McGrath, 2010).

Central to such negative impact involves overlapping cellsignalling controls and molecular

mechanisms (Zhu, 2002; Pandey et al., 2011; Pandey, 2015).Table 2 summarizes various

efforts on elucidating mechanisms and molecularmanipulation of tomato for tolerance to

abiotic stresses, some of which are further discussed below.

Table 2 Genetic engineering of tomato for tolerance toabiotic stress

Gene and source Description Trait/phenotype conferredReference

d-Galacturonic acid

reductase GalUR

Fragaria x ananassa

Strawberry Overexpression of GalUR driven by CaMV 35S(Cauliflower mosaic virus 35S promoter) Abiotic stresstolerance, particularly salt tolerance (200 mM), elevatedascorbic acid content Lim et al., 2016

SOS2L1

Salt overly sensitive

Malus x domestica

Apple Overexpression of full-length MdSOS2L1 cDNA drivenby CaMV 35S Salt tolerance (300 mM NaCl) Hu et al.,2016

WD6

(family of Trp-Asp

WD-repeat proteins)

Solanum lycopersicum Constitutive expression byAgrobacteriummediated transformation Drought and salttolerance Yang et al., 2015

NHX2

Na + /H + Exchanger

S. lycopersicum LeNHX2 ion transporter overexpressiondriven by CaMV 35S Salt tolerance (120 mM NaCl), higherNa + /H + and K + /H + transport activity in rootintracellular membrane vesicles, two fold higher K +depletion rate, half cytosolic K + activity, enhanced HAK(high-affinity K + uptake system) expression under K +-limiting conditions Huertas et al., 2013

Table 2 (Continued)


BADH

Betaine aldehyde

dehydrogenase

Suaeda liaotungensis Overexpression of BADH gene drivenby CaMV 35S and P5 promoters Salt tolerance (200 mM NaCl)Wang et al., 2013

GlyI and GlyII

Glyoxalase I and

glyoxylase II

Brassica juncea and

Pennisetum glaucum Overexpression of BjGlyI and PgGlyIIgenes under CaMV 35S Engineering of glyoxyalasedetoxification provides salt tolerance (800 mM NaCl)Álvarez-Viveros et al., 2013

SOS2

S. lycopersicum SlSOS2 ion transporter overexpressiondriven by CaMV 35S Salt tolerance (120 mM NaCl), higherNa + content in leaves and stems, no differences in K +content relative to untransformed plants Huertas et al.,2012

Hem1

Saccharomyces

cerevisiae Hem1 gene driven by the light-responsive HemA1promoter from Arabidopsis thaliana Improved salt tolerance(200 mM NaCl) Li et al., 2012

Na + /H + antiporter

NHX

P. glaucum

Vacuolar H +

pyrophosphatase AVP1

Arabidopsis thaliana Co-expression of PgNHX1 and AVP1driven by CaMV 35S Tolerance to 200 mM NaCl, accumulatedproline and Na + , 1.4 and 1.5 times, respectively, thansingle gene transformants Bhaskaran and Savithramma,2011

Xyloglucan endo-trans

gluco-sylase/hydrolase

(XTH3)

Capsicum annum Ectopic overexpression of full-lengthCaXTH3 cDNA driven by CaMV 35S Increased tolerance tosalt (100 mM) and drought stresses Choi et al., 2011

codA

Choline oxidase

Arthrobacter globiformis Expression of codA gene fusedwith chloroplast targeting transit peptide driven byCaMV 35S Accumulation of glycinebetaine in leaves up to297 nmol g − 1 fresh weight, provides salt (200 mMNaCl) and water stresses Goel et al., 2011

SOS1

S. lycopersicum Silencing of SlSOS1 transporter by RNAitechnology Transgenic plants with reduced expression ofSlSOS1 showed reduced growth relative wild type in salineconditions. They accumulated higher Na + in leaves androots than stems under salt stress Olías et al., 2009(Continued)

Table 2 (Continued)


TPS1

Trehalose-6-phosphate

synthase

S. cerevisiae Overexpression of TPS1 gene driven by CaMV35S Increased tolerance to drought, salt and oxidativestress; abnormal plant morphology Cortina andCulianez-Macia, 2005

BADH

Betaine aldehyde

dehydrogenase

Atriplex hortensis Overexpression of BADH gene driven byCaMV 35S Salt tolerance (120 mM NaCl) Jia et al., 2002

NHX1

A. thaliana Overexpression of At-NHX1 gene driven by CaMV35S Salt tolerance (up to 200 mM NaCl), high Na +accumulation in leaves, very low levels in fruits,increased growth, flower and seed production Zhang andBlumwald, 2001

betA

Choline dehydrogenase

Escherichia coli TG1 Overexpression of beta gene under thecontrol of CaMV 35S Increased osmotic adjustment abilityof transgenics relative to wild type, salt tolerance at200 mM NaCl Wang et al., 2001

HAL1

Halotolerance gene

S. cerevisiae Overexpression of HAL1 open reading frameunder CaMV 35S Modulate cation transport systems, Na + andK + homeostasis, reduced growth, fruit yield reductionin normal conditions but 27% increase under salt stressGisbert et al., 2000 (short-term study); Rus et al.,2001 (long term study)

BADH-1

Betaine aldehyde

dehydrogenase

Sorghum Production of hairy roots by transformation with

Ri plasmid Maintenance of osmotic potential under saltstress Moghaieb et al., 2000

HAL2

Halotolerance gene

S. cerevisiae Overexpression of HAL2 gene driven by CaMV35S with double enhancer and synthetic Alfalfa mosaicvirus RNA4 leader sequence Salt tolerance (175 mM NaCl)Arrillaga et al., 1998

ICE1

[Inducer of CBF

(C-repeat binding factor

expression)]

A. thaliana Overexpression of ICE1 Tolerance to lowtemperature stress, high proline, peroxide content andcatalase activity in transgenics but low malondialdehydecontent Juan et al., 2015

CRT/DRE-binding

factor1

A. thaliana Expression of AtCBF1 driven by stressinducibleABRC1 promoter from barley HAV22 gene Enhanced toleranceto chilling, water deficit and salt stress Lee et al.,2003a

4.1 Salinity stress tolerance

Salinity negatively affects productivity and quality ofcultivated crop plants. It is anticipated

that salinization of arable land will increase from 20%presently to 50% by the year 2050

(Wang et al., 2003), perhaps due to increased use ofunderground water, lack of freshwater

and flawed fertilization practices (Yu et al., 2012). Salttolerance is a complex trait and

response to salt stress is attuned by agronomic,physiological, developmental, genetic

and environmental factors (Foolad, 2004). Studies onmitigating salinity stress in plants

have involved following strategies.

4.1.1 Ion transport proteins

Ion transport proteins integral to plant plasma andtonoplast membranes are important

for maintenance of intrinsic ion balance in a cell.Transporters that maintain Na + balance in

plants include NHX (Na + /H + exchanger), SOS (salt overlysensitive) and HKT (high-affinity

potassium transporter).

Roots of T3 homozygous tomato plants with a singleinsertion of LeNHX2 under CaMV

35S promoter, an endosomal class II NHX transporter,accumulated LeNHX2 transcripts

under stress by 120 mM salt. These transgenic plantsyielded higher shoot fresh weight

under salt treatment; however, under K + -limitingconditions shoot fresh weight decreased

relative to the wild-type control plants. When external K +availability is low, the decrease

of cytosolic K + caused by LeNHX2 overexpression couldlead to the higher LeHAK5 (high

affinity K + uptake system) expression in transgenicplants relative to untransformed control

Table 2 (Continued)


SAMDC

S-adenosylmethionine

decarboxylase

S. cerevisiae Agrobacteriummediated leaf disctransformation Accumulation of spermidine and spermineunder high temperature stress, high antioxidant enzymeactivity, protection of membranes from lipid peroxidationCheng et al., 2009

Osmotin

Tobacco Overexpression of osmotin gene driven by CaMV 35STransgenic lines showed higher relative water content,chlorophyll content, proline content and leaf expansionthan wild type under salt and drought stress Goel et al.,2010

OaAANAT

Arylalkylamine

N-acetyltransferase

OaHIOMT

Hydroxyindole

O-methyltransferase

Ovis aries (sheep) Expression of OaAANAT and OaHIOMTgenes driven by constitutive CaMV 35S Drought tolerancein transgenic lines expressing OaHIOMT Wang et al., 2014

plants. Overexpression of LeNHX2 resulted in increaseduptake of K + by epidermal root

cells. Plant growth is inhibited under K + deficiency andsalt tolerance is imparted due to

modified K + uptake (Huertas et al., 2013). Overexpressionof Arabidopsis vacuolar Na + /

H + antiport (AtNHX1) enabled transgenic tomato plants togrow, flower and produce fruit

in the presence of 200 mM NaCl (Zhang and Blumwald, 2001).Notably, high amounts of

sodium accumulated in leaves but not the fruit.

Activation of Ca 2+ -dependent SOS signalling is a keymolecular mechanism to prevent

intracellular accumulation of toxic amounts of Na + (Zhu,2002) with SOS1, SOS2 and SOS3

as the functional components (Zhu et al., 1998).Compartmentalization of Na + in plant

stems as opposed to roots and leaves is a common mechanismused by SOS system

to help plants evade effects of high salt stress.Decreasing SlSOS1 transcript population

in transgenic tomato by RNAi technology changed organpartitioning of Na + with more

accumulation in leaves and roots and lesser in the stem(Olías et al., 2009) confirming the

function of SOS1. Ectopic expression of MdSOS2L1, a CIPKprotein kinase (calcineurin

B-like protein-interacting protein kinase), in tomatoenabled tolerance to NaCl at 300

mM concentration (Hu et al., 2016). These transgenictomatoes contained higher levels

of procyanidin and malate, and produced less reactiveoxygen species (ROS) such as

hydrogen peroxide that may have contributed to containingoxidative damage. Over

expression of SlSOS2, a candidate gene believed to beinvolved in regulating vacuolar

Na + /H + exchange, in tomato conferred salinity tolerance(at 120 mM NaCl) via Na +

extrusion from the root, accumulation in aerial parts,active loading of Na + into xylem, and

compartmentalization of Na + and K + (Huertas et al.,2012). These transgenic tomato plants

also had higher transcript levels of the Na + , K + /H +antiporter LeNHX4 in roots, stems and

leaves, and higher Na + /H + antiport activity in root

tonoplast vesicles.

4.1.2 Osmotic homeostasis

Whether higher plants possess an osmoregulatory mechanismto cope up with water

stress was reviewed (Schobert, 1977) and it was proposedthat polyols and proline

play a key role in osmotic adjustments. Mannitol, a sugaralcohol synthesized from

fructose by mannitol-1-phosphate dehydrogenase (mtlD),plays an important role in the

osmoregulation of plants. Thus, transgenic tomato plantsthat constitutively expressed

E. coli mtlD gene were found to develop tolerance tochilling, drought and salinity stress

(Khare et al., 2010).

Osmotin or osmotin-like protein is a member of the PR-5family (class 5 pathogenesis

related) induced in plants upon exposure to abiotic andbiotic stresses and implicated in

providing osmotolerance (Singh et al., 1985, 1987;Barthakur et al., 2001). It is constitutively

present in tomato grown under sustainable agriculturalpractices and provides tolerance

against biotic stress (Kumar et al., 2004, 2005).Overexpression of tobacco osmotin gene in

tomato conferred increased tolerance to salt and droughtstress (Goel et al., 2010) in these

transgenics. These plants had higher relative watercontent, chlorophyll, proline and leaf

expansion than the wild-type plants when exposed to stress.Osmotin provides protection

to native proteins during stress and repairs denaturedproteins (Pandey et al., 2011). Over

expression of tobacco osmotin gene is also believed tomodulate transcriptional profiles

of other pathogenesis-related (PR) genes such as PR1 andPR4. These PR genes may

provide resistance to pathogens since they are increased intomato seedlings treated with

exogenous salicylic acid and benzo (1,2,3)thiodiazole-7-carbothioic acid S-methyl ester

(Fiocchetti et al., 2006).

4.1.3 Production of ROS scavengers

Oxidative stress in plant cells upon exposure to highsaline conditions results in increased

production of ROS (Mittler et al., 2004) and subsequentoxidative damage, characterized

by lipid peroxidation and fatty acid de-esterification, incell membranes (Arora et al., 2002).

Genes imparting salt tolerance seem to be present in bothhalophytes and glycophytes;

however, they are regulated differently in variedenvironments (Himabindu et al., 2016).

Salt-responsive genes from halophytes have been engineeredin various plant systems,

including tomato (Himabindu et al., 2016). Notably,expression of genes providing salt

tolerance is advantageous when transgenes are fused tostress-inducible promoters as

the negative effects on the transgenic plants are preventedin the process. For instance,

expression of BADH (betaine aldehyde dehydrogenase) genedriven by P5 promoter

(from Suaeda liaotungensis) was used to develop tomatotransgenics that were tolerant to

sodium chloride at 200 mM (Wang et al., 2013).

Transgenic tomatoes expressing strawberry GalUR(d-galacturonic acid reductase)

gene were more tolerant to abiotic stresses induced bymethyl viologen (20 mM), NaCl

(200 mM) and mannitol (up to 300 mM) than the controlplants (Lim et al., 2016). These

transgenic lines contained higher ascorbic acid andchlorophyll contents and low levels of

malondialdehyde under salt stress. Higher expression levelsof antioxidant genes such as

ascorbate peroxidase (AOX) and catalase (CAT) were alsofound in the transgenic plants

compared to controls.

4.2 Chilling stress tolerance

Tomato is cold sensitive and suffers chilling injury below13°C. At such cold temperatures

the plant growth and yield are compromised (Lin et al.,2000). The identity of cold-induced

genes have come to light in numerous works of researchers,implicating diverse players,

including transcription factors such as CBF(CRT/DRE-binding factor), the disaccharide

trehalose and reduced glutathione (GSH) (Mackenzie et al.,1988; Thomashow, 1999;

Herbette et al., 2005; Li et al., 2010). A composite plantdefence response to chilling

stress involves the regulatory molecular cascade, whichincludes cold-responsive

genes/transcription factors ICE1 (inducer of CBF3expression1), MYB, MYC and CBF

(C-repeat binding factor), along with ubiquitin E3 ligaseHOS1 and SUMO E3 ligases

SIZ1/SIZ2 (Thomashow, 2010; Medina et al., 2011; Knight andKnight, 2012). Low

temperature-responsive model for Arabidopsis involves ICE1that encodes a MYC-like

basic helix–loop–helix transcription factor that, in turn,activates CBF3/DREB1A and COR

genes (Chinnusamy et al., 2003).

The plant expression construct p3301 harbouring ArabidopsisICE1 transcription

factor was overexpressed in tomato cultivar rhubarb withthe aim of achieving cold

tolerance (Juan et al., 2015). The transgenics were given alow-temperature stress that

led to an increase in peroxidase and catalase activitiesalong with proline content, with

the oxidative stress molecule malondialdehyde being atlower concentrations than the

control. Transgenic tomato cultivar Pusa Ruby transformedto express tobacco osmotin

gene was subjected to cold temperature treatment (4°C for 2and 24 h) and it led to

higher expression of additional stress-responsive genes,namely, CBF1, P5CS, and APX

and increased accumulation of free proline and ascorbicacid content (Patade et al., 2013).

A revealing finding upon analysis of ectopically expressedICE1, which led to enhanced

tolerance to cold stress, was the concomitant increase inarginine decarboxylase (ADC)

transcripts and levels of free polyamines (Huang et al.,2015). Polyamines are biogenic

amines that impart protection to plants against differentabiotic stresses (Mattoo, 2014;

Mattoo et al., 2015). Interestingly, while studyingchilling temperature responses of

tomato fruit, a PR protein, PR1b1 protein, was found topredominantly accumulate in

fruit brought to room temperature after two weeks ofexposure at 2°C. In tomato lines

engineered for the ripening-associated accumulation ofhigher polyamines, spermidine

and spermine, the PR1b1 protein remained abundant inre-warmed chilled fruit for an

extended period as compared to control fruit deficient inthese two polyamines (Goyal

et al., 2016). Further, a positive correlation was foundbetween increase in the PR1b1

protein and gene transcripts with the transcripts of MYC2,MYB1, CBF1 and glucose

6-phosphate dehydrogenase (G-6-P DH) transcripts, andsalicylic acid levels in the high

spermidine/spermine transgenic tomato fruit (Goyal et al.,2016). It was proposed that

polyamine-mediated accumulation of PR1b1 protein inre-warmed chilled tomato could be

a pre-emptive plant defence mechanism related to coldstress-induced disease resistance

(SIDR) phenomenon, function and mechanisms of which are yetto be determined (Moyer

et al., 2015).

Trehalose, an osmoprotectant, is yet another mitigator ofchilling stress through

protection of membrane proteins, stabilization of nativeprotein state, reduction in

aggregation of denatured proteins and prevention of celldesiccation (Crowe et al., 1984;

Singer and Lindquist, 1998). Thus, rice TPP1(trehalose-6-phosphate phosphatase 1)

overexpression augmented the cold tolerance of rice(Pramanik and Imai, 2005) while

yeast TPS1 (trehalose-6-phosphate synthase 1) expression intomato imparted drought

tolerance (Cortina and Culianez-Macia, 2005). Similarly,overexpression of mouse GSH

peroxidase in transgenic tomato plants led them to retainnormal photosynthetic activity

under chilling stress compared to wild-type plants(Herbette et al., 2005).

4.3 Drought tolerance

Plants that grow in arid conditions have evolved a highlyexpanded root system,

adaptations like spines to reduce transpiration and waxycuticles on leaves to evade

scarcity of water (Kramer and Boyer, 1995). ArabidopsisCBF1 overexpressed in tomato

imparted resistance to drought stress (Hseih et al., 2002).A slight increase in water stress

tolerance was observed in transgenic tomato expressing ahighly heat-stable Populus

tremula 66-kD protein (Roy et al., 2006). Arabidopsisvacuolar H + -pyrophosphate

(AVP1) expression in tomato that resulted in salt- anddrought-tolerant phenotype was

accompanied with an increase in root biomass (Park et al.,2005). Relatively more drought

tolerant transgenics than the wild-type controls wereobtained when Saccharomyces

cerevisiae TPS1 gene was introduced into tomato, albeitwith abnormal changes in

plant morphology (Cortina and Culianez-Macia, 2005).Constitutive expression of

sheep arylalkylamine N-acetyltransferase in tomato imparteddrought tolerance to the

transgenic lines (Wang et al., 2014).

4.4 High temperature tolerance

Chaperones or heat shock proteins are well-known componentsof plant machinery to

respond to high temperature stress (Swindell et al., 2007).Tomato fruits transformed with

Arabidopsis heat shock factor (hsf) gene were tolerantequally to high (47°C) and low (�2°C)

temperatures during storage periods of up to 4 weeks (Lurieet al., 2003). Overexpression

of Arabidopsis ERECTA (ER) in transgenic tomato and ricelines improved their tolerance

to high temperature, both in greenhouse and field tests atmultiple locations in China,

over several seasons, and had increased biomass (Shen etal., 2015). These researchers

used S. pimpinellifolium (accession LA1589), which istemperature sensitive, compared

with modern-day varieties of tomato to overexpress ER underCaMV35 promoter. ER over

expression in tomato resulted in two times larger leafsize, decreased stomatal density,

decreased stomatal conductance and increased transpirationefficiency relative to wild

type. The transgenic tomatoes could withstand temperatureregime of 40 o C/28 o C (day/

night) for 10 days in a growth chamber.

As mentioned above, polyamines are important regulators in

plant biology and

defence providers. They regulate multiple biologicalprocesses in plants, including

stomatal opening, stress responses and interaction withother plant hormones (Kumar

et al., 2006; Liu et al., 2007; Yang et al., 2007; Handaand Mattoo, 2010; Anwar et al.,

2015). Overexpression of yeast S-adenosylmethioninedecarboxylase in tomato boosts

endogenous concentrations of polyamines, and suchtransgenic plants have been

shown to have superior tolerance to high temperature stressthan the control plants

(Cheng et al., 2009).

5 Biotic stress tolerance

Biotic stress due to bacterial, viral, fungal and insectpathogens devastates the yield and

quality of crop plants, including tomatoes. Molecularmarkers have provided fundamental

data regarding pathogen population diversity and evolutionimportant for disease control

in different crop plants (De Giovanni et al., 2004; Kaur etal., 2005; Purkayastha et al.,

2006, 2008). In tomato, 40 widely spread diseases areknown, most of which are caused by

either bacteria or fungi (Khaliluev and Shpakovskii, 2013).Pathogen recognition is followed

by a rapid oxidative burst typified by production ofreactive oxygen intermediates such

as superoxide anion (O 2 ), hydroxyl radicals (OH) andhydrogen peroxide (H 2 O 2 ), which

may control pathogen resistance response and acquiredimmunity (Jabs, 1999; Grant

and Loake, 2000; Bergougnoux, 2014). The response topathogen attack is mediated

by active and passive defences including hypersensitivereaction, programmed cell

death/apoptosis, defence genes expression (PR proteins),phytoalexins, phytoanticipins,

phenolics and ROS. Table 3 lists selected examples ofgenetic engineering of tomato to

mitigate biotic stresses.

5.1 Resistance to bacterial diseases

Overexpression of potato polyphenol oxidase (StPPO) gene intomato imparted resistance

to Pseudomonas syringae pv. tomato, causal agent ofbacterial spot disease, in terms

of both number and area of lesions corresponding to a100-fold reduction in bacterial

population in infected leaves (Li and Steffens, 2002).These plants accumulated quinones

that had a cytotoxic effect on pathogens. In contrast,suppression of PPO gene in tomato

by antisense StPPO cDNA dramatically decreased theoxidation of caffeic acid and

increased the plant’s susceptibility to this pathogen(Thipyapong et al., 2004), suggesting

the involvement of phenolic oxidation in disease resistancein tomato. The transgenic

tomato plants expressing a human cathelicidin antimicrobialpeptide (hCAP18/LL-37)

Table 3 Genetic engineering of tomato for tolerance tobiotic stress


Cathelicidin

antimicrobial peptide

Homo sapiens Overexpression of hCAP18/LL-37 (fused tosignal peptide from pea vc-2 gene) driven by PGD1promoter, extracellular localization of mature proteinResistance to bacterial soft rot and bacterial spotdiseases, high expression of PR protein, LTP (proteaseinhibitor contains lipid transfer protein) and AFP1(cysteine-rich antifungal protein precursor) genes Jung,2013

MAP kinase Silencing of SlMAPKKKɛ Disruption ofresistance against Xanthomonas campestris andPseudomonas syringae Melech-Bonfil and Sessa, 2010

Cys-2/His-2-zinc

finger protein-TF

(pathogenesis-induced

factor)

Capsicum anum Overexpression of CaPIF1 driven by CaMV 35SResistance to Pseudomonas syringae pv. tomato DC 3000,tolerance to cold stress Seong et al., 2007

Polyphenol oxidase

Solanum tuberosum Suppression of StPPO by antisensetechnology driven by CaMV 35S Increased susceptibility toP. syringae pv. tomato Thipyapong et al., 2004

Magainin-cationic

antimicrobial peptide

Synthetic Overexpression of MSI-99 (fused to signalpeptide from pea vicilin gene) driven by EnhancerCaMV35S, targeted expression in extracellular spacesIncreased resistance to P. syringae pv. tomato (bacterialspeck pathogen), no cytotoxic effects in transgenicplants Alan et al., 2004

Glycoprotein,

antibacterial

H. sapiens Lactoferrin (LF) Partial resistance toRalstonia solanacearum (bacterial wilt) Lee et al., 2002

Polyphenol oxidase

S. tuberosum Overexpression of StPPO driven by CaMV 35SIncreased resistance to P. syringae pv. tomato Li andSteffens, 2002

Serine/threonine

protein kinase (R gene)

S. lycopersicum Overexpression of SlPTO driven by CaMV35S Resistance to Xanthomonas campestris pv. vesicatoriaand Cladosporium fulvum Tang et al., 1999

Table 3 (Continued)


Hevein-like protein

(PR4 family)

Pharbitis nil Overexpression of Pn-AMP2 driven by CaMV35S Enhanced resistance to Phytophthora capsici andFusarium oxysporum Lee et al., 2003b

Bt Cry2A

Bacillus thuringiensis Overexpression of Bt Cry2A genedriven by CaMV 35S Resistance to neonate larvae ofHelicoverpa armigera in laboratory conditions Hanur etal., 2015

Chymotrypsin inhibitor

S. lycopersicum Overexpression of JIP21 (jasmonicinducedprotein) gene driven by CaMV 35S Increased mortality oflepidopteran Spodoptera littoralis larvae Lison et al.,2006

Chitinase Win6

Poplar Potato virus X CP (coat protein) promoter: win6Resistance to Colorado potato beetle (Leptinotarsadecemlineata) larvae Lawrence and Novak, 2006

Arginase

S. lycopersicum Overexpression of ARG2 gene driven byCaMV 35S Increased resistance to Manduca sexta larvae Chenet al., 2005

Pin and

carboxypeptidase

inhibitors

S. tuberosum Tissue-specific expression of serineprotease inhibitor, PI-II driven by StLS1 promoter (leafand stem specific) and carboxypeptidase inhibitor (PCI)driven by rbsc-1A Increased resistance to Heliothisobsoleta and Liriomyza trifolii Abdeen et al., 2005

Bt Cry1Ac

B. thuringiensis Overexpression of Bt Cry1Ac gene drivenby CaMV 35S Resistance to larvae of Helicoverpa armigerain leaves and fruits Mandaokar et al., 2000

d-Endotoxin gene

B. thuringiensis subsp.

tenebrionis Overexpression of Bt toxin gene driven byCaMV 35S Resistance to Colorado potato beetle(Leptinotarsa decemlineata) larvae Rhim et al., 1995

Systemin

S. lycopersicum Silencing prosystemin gene driven by CaMV35S by antisense technology Decrease in resistance toManduca sexta (tobacco hornworm) larvae via reduction inproteinase inhibitors I and II Orozco-cardenas et al.,1993

were significantly resistant to bacterial soft rot andbacterial spot with concomitant strong

expression of PR protein, LTP and AFP1 genes. Transgenictomato leaf protein extracts

limited the growth of P. carotovorum ssp. carotovorum to15%, and that of Xanthomonas

campestris pv. vesicatoria to 35% (Jung, 2013). MAP

(mitogen-activated protein)

kinase signalling pathways are associated with plantimmunity with their involvement

in hypersensitive response cell death and resistanceagainst Gram-negative bacterial

pathogens in tomato. Silencing of SlMAPKKKe in tomatodisrupted resistance against

X. campestris and P. syringae (Melech-Bonfil and Sessa,2010). Downregulation of a

peroxidase gene Ep5C by its antisense RNA impartedresistance to P. syringae pv. tomato

(Coego et al., 2005).

5.2 Resistance to fungal and viral diseases

PR proteins and antimicrobial peptides are effective atmicromolar concentrations (and

non-toxic to animals and humans) by imparting resistance tofungal (and bacterial) diseases

in plants (Khaliluev and Shpakovskii, 2013).Agrobacterium-mediated transformation

of tomato cultivar A53 with dual PR genes, tobacco AP24osmotin and bean chitinase,

produce transformants with improved Fusarium wiltresistance (Ouyang et al., 2005).

Resistance genes (R genes) provide plants the tools forpathogen effector recognition and,

therefore, race-specific immunity. Transgenic tomatoexpressing S-receptor-like kinase

(SRLK) genes I, I-2 and I-3 imparted tolerance to F.oxysporum f. sp. lycopersici races 1,

2 and 3, respectively (Catanzariti et al., 2015). A 36% to58% reduction of Fusarium wilt was

demonstrated when tobacco class I chitinase and1,3-glucanase genes were introduced

into tomato (Jongedijk et al., 1995).

Agrobacterium-mediated transformation of tomato with acidicendochitinase (pcht28)

from wild S. chilense developed resistance againstVerticillium dahliae (races 1 and 2)

tested in greenhouse (Tabaeizadeh et al., 1999). Also,transgenic tomato fruits expressing

hevein (HEV1) were less prone to the fungal pathogenTrichoderma hamatum (Lee and

Raikhel, 1995), while hevein-like chitin-binding proteinPnAMP2 from Pharbitis nil conferred

resistance to Phytophthora capsici in transgenic tomato(Lee et al., 2003b). Chitin-binding

protein genes from Amaranthus caudatus (ac) and hevein-likeantimicrobial protein from

Stellaria media (amp1, amp2) in transgenic tomato plantsaugmented their resistance to

late blight.

In a relatively uncommon instance of genetic engineering,expression in tomato of a

single gene involved in ergosterol biosynthesis, C-5 steroldesaturase (FvC5SD), from

Flammulina velutipes elevated protection againstSclerotinia sclerotiorum through a

thicker waxy cuticle barrier to entry (Kamthan et al.,2012). In addition, it also enabled

drought tolerance, an increase in iron as well aspolyunsaturated fatty acid content in

tomato. The inhibitor-of-virus replication (IVR) gene fromtobacco introduced into tomato

cultivar VF36 conferred partial resistance to severalfungal pathogens, namely, Alternaria

alternata, Pythium aphanidermatum and Rhizoctonia solani atseedling stage and to

A. solani (early blight) and Oidium neolycopersici (powderymildew) in mature plants

(Elad et al., 2012).

Resistance to tomato mosaic virus (TMV) and to hightemperature was engineered into

tomato by cloning Arabidopsis NPR1 gene (Lin et al., 2004).In addition to the resistance

to TMV, these transgenics also displayed resistance toFusarium wilt, grey leaf spot (fungal

diseases), bacterial wilt and bacterial spot. Transgenictomatoes expressing intron-hairpin

construct derived from C1 gene enabled post-transcriptionalsilencing of tomato yellow

leaf curl virus (Fuentes et al., 2006). Overexpression ofthe SlAOX gene, encoding a

tomato mitochondrial alternative oxidase (AOX), enhancedtolerance to spotted wilt virus

in tomato (Ma et al., 2011).

5.3 Resistance to insects and nematodes

One of the early reports of field testing of transgenictomato plants was the one

expressing insecticidal protein from Bacillus thuringiensisvar. kurstaki HD-1 specific

against lepidopterans (Delannay et al., 1989). Thesetransgenic plants were resistant to

leaf damage by Manduca sexta, Heliothis zea and Keiferialycopersicella. Plant defence

systems are equipped with proteinase inhibitors andsecondary metabolites for protection

against insects. Tomato leaves contain systemin, an 18amino acid polypeptide, which

induces proteinase inhibitors, and is a systemic woundsignal, likely mediates jasmonate

signalling pathway in response to an insect attack. Plantproteinase inhibitors inhibit the

activity of gut insect proteases. Proteases in the gut ofinsects break down proteins to

produce amino acids as food. Examples include lepidopteranserine proteinases and

coleopteran cysteine and aspartic proteinases. To managedefence against insects,

transgenic tomato plants were developed that expressed twopotato protease inhibitors

(Abdeen et al., 2005). A serine proteinase inhibitor,PI-II, and a carboxypeptidase inhibitor,

PCI, in combination, provided strong resistance againstHeliothis obsoleta and Liriomyza

trifolii larvae, respectively, in homozygous transgenics.The South Indian tomato cultivar,

Arka Vikas, was transformed using Agrobacterium carrying aBtCry2A construct to create

transgenics resistant to damage caused by neonate larvae ofHelicoverpa armigera

(Hanur et al., 2015).

Root-knot nematode (RKN) pathogen, Meloidogyne incognita,causes major economic

losses in agriculture. Reducing expansin gene expression intomato gall cells by antisense

LeEXPA5 (tomato expansin isoform; expansin precursor 5locus) was found to limit

pathogenesis by RKN, which was attributed to inability ofthe nematode to complete

its life cycle (Gal et al., 2006). RKN control is alsopossible by plant defence genes, for

instance, proteinase inhibitors. Cysteine proteinaseinhibitor CeCPI from Colocasia

esculenta and fungal chitinase PjCHI-1 from Paecilomycesjavanicus were overexpressed

together in tomato, and the transgenic plants had anunfavourable effect on chitin content

of RKN eggs as well as on embryogenesis (Chan et al., 2015).

6 Tomato as a model system for biopharming

Tomato has been used as a model plant also for productionof oral vaccines, which

are designed to provide an affordable and easily accessiblepreventative and curative

medical care for the needy. Plant systems-based recombinantproteins and vaccines

combine the therapeutic power of antigenic peptidesexpressed within fruit tissue

with low cost of production, safety, easy transportationand availability (Chen et al.,

2009; Ahmad et al., 2012; Aryamvally et al., 2016). Someinteresting examples of

edible tomato vaccines are presented below. Tomato issuitable for production of

oral vaccines as fresh edible fruits, because of relativelyefficient transformation,

stackability of genes via crossing, large-scale greenhouseproduction and processing

technology (cholera toxin B subunit expression, Jani etal., 2002, 2004; Warzecha and

Mason, 2003). Challenges of edible vaccine production infruits include the presence

of suboptimal antigen concentration, as ripe tomato fruitscontain �0.7% protein and

expression of foreign proteins to high levels is limited(Youm et al., 2008). Use of

stronger promoters, tissue-specific promoters, signalpeptides and codon optimization

have been applied to overcome these challenges(Lauterslager et al., 2001; Sojikul et

al., 2003; Tackaberry et al., 2003; Youm et al., 2005).Utilization of strong adjuvants such

as b subunit of the cholera toxin, alongside the primaryantigen molecule may bolster

the immunogenic response (Youm et al., 2008; Baldauf etal., 2015). Nanotechnology

is another avenue for novel ways to thwart difficulties inthis field in terms of site

specific delivery of the oral vaccine (Zhu and Berzofsky,2013). Plant products used as

a source of pharmaceutical proteins have to be keptseparate from mainstream food

supply (Warzecha and Mason, 2003).

Tomato was successfully transformed with E. coliheat-labile enterotoxin B subunit

to produce the LTB (E. coli heat-labile enterotoxin Bsubunit) protein. The protein was

found to form active pentamers using an ELISA assay (Loc etal., 2014). Also, transgenic

tomatoes engineered to express synthetic DPT (diphtheria,pertussis and tetanus)

vaccine as a single gene were successfully used to immunizemice orally (Soria-Guerra

et al., 2007). Significant IgA and IgG antibody levels werefound in the intestine but

response was weaker in tracheopulmonary fluids. The resultsof this study pointed out

the availability of a therapeutic tomato that could replacethe traditional triple vaccine in

the near future. Transgenic tomato expressingcodon-optimized thymosin a I concatamer

(an immune system synergist) were tested and found tostimulate the proliferation

of mice spleenic lymphocytes. Mature fruits were found toaccumulate protein up to

6.1 mg g −1 fresh weight (Chen et al., 2009). ORF2 partialgene of hepatitis E virus and

large surface antigen gene of hepatitis B virus wereengineered in transgenic tomato

leaves and fruits as viral antigens (Ma et al., 2003; Louet al., 2007). A key player in the

development of Alzheimer’s disease, human b-amyloid protein(Ab), was overexpressed

as trimer to pentamer tandem repeats under the control ofCaMV 35S promoter in

tomato (Youm et al., 2008). Balb/c mice immunized orallywith total soluble extracts

from these transgenic tomatoes and boosted by the syntheticAb peptide emulsified in

alum, elicited an immune response and the immunized miceproduced serum antibodies

against the Ab antigen as confirmed by western blots andELISA. These preliminary

results are very promising for developing novel antigensfor immunization.


There has been a phenomenal advancement in thebiotechnology of agricultural crops.

This revolution has greatly modified and reduced the use ofpesticides in the production of

agronomical crops, particularly corn and soya bean, over90% of which are now genetically

enhanced by biotechnology. As was made apparent here,tomato is a good model system

to test various axioms to enhance crop productivity andimprove fruit quality, including shelf

life and nutritional attributes. These biotech-enhancedcrop varieties have gone through

laborious field tests for crop performance and productionstrategies, and yielded huge

amounts of data on the use of biotechnology for enhancingcrop productivity and producing

value-added crops. Thus, biotechnology tools have led tothe development of novel tomato

genotypes that include enhanced abiotic stress tolerancewith a great potential to overcome

the present and future challenges imposed by global climatechange; improved resistance

to biotic stress to reduce devastating losses due todiseases; enhancement in fruit shelf life

and quality to reduce post-harvest losses; boosted levelsof many phytonutrients with the

potential for human health and wellness promotion –examples include folates, anthocyanins,

carotenoids and anti-ageing polyamines, particularly tomeet recommended daily allowance

and reduce physiological disorders in human population;novel plants that can become

factories to produce pharmaceuticals including vaccines.

Translation of biotechnology advancements for developinghorticultural crops should

lead to the emergence of ‘super’ speciality crops, which wecan only imagine today.

However, in spite of this extensive research carried outworldwide independently by

academicians, public and privately supported researchers,and industry has had limited

commercial translation due to unfounded and non-scientificperceptions causing lack

of support from retailers and food producers (Aerni, 2013).A recent report published

by Committee on Genetically Engineered Crops, The NationalAcademies of Sciences,

Engineering and Medicine (2016) analysed about 900 researchpublications on commercial

crops developed through genetic engineering and foundpositive effects on human

health and agriculture (www.nationalacademies.org). Noevidence of environmental

problems due to cultivation of GE crops was found. Emergingtechnologies such as

CRISPR/Cas9 (Barrangou et al., 2007) and synthetic biologyprovide great precision for

organismal genome improvement, including making singlenucleotide changes as do

radiation and chemical methods for mutation. The committeenoted that both genetic

engineering and conventional breeding processes should beevaluated for potential

harm to humans and environment. Organized and stringentregulatory system and

rigorous risk assessment, for demonstrable safety andefficacy of genetically engineered

products and not the process, are central to shifting theattention of the public from the

technique per se to the advantages offered by novel traits.It is, however, clear that this

technology is here to stay and would greatly help inmaintaining food security to ever

increasing world population.


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9 Acknowledgements

A. K. H. research was supported by USDA/NIFA2010-65115-20374 and USDA/NIFA 2012

67017-30159. Trade names or commercial products mentionedin this publication are only

to provide specific information and do not imply anyrecommendation or endorsement by

the authors. USDA is an Equal Employment Opportunityprovider.

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12 Chapter 12 Understanding and improvingthe shelf life of tomatoes

1 Introduction

Shelf life of ripe fruits, especially of the climacterictype, represents one of the most

significant agronomical traits that determine the fruitquality during post-harvest marketing

and impacts the economic returns to the producer and seller(Peralta and Spooner, 2006;

Paliyath et al., 2009; Nath et al., 2014). Substantialfruit losses occur during the post

harvest period largely due to the highly perishable natureof horticultural produce (Kitinoja

et al., 2011). The physiological and biochemical changesthat transform an unripe fruit to

a desirable, edible ripe fruit are also associated withreducing fruit shelf life, increasing

shrivelling (water loss), surface cracking, prematuresenescence and microbial decay,

thereby lowering the acceptability of ripe fruits.Significant attention has been paid to the

fruit-softening process as the fruit structure weakens andbecomes more susceptible to

mechanical bruising and decay symptoms due to post-harvestpathogens. A large number

of cell wall hydrolytic and lyase enzymes are produced denovo during fruit ripening, which

have been implicated in textural changes and fruitsoftening. However, jury is still out about

their molecular role in fruit texture and softening (Negiand Handa, 2008; Seymour et al.,

2012). The ripening-associated changes in fruit membranealso play significant roles in

the production of volatile compounds, enhancing theorganoleptic characteristics of fruits

(Kausch et al., 1997; Palma et al., 2011; Whitaker et al.,2011; Osorio et al., 2013). Membrane

integrity was found to be intact during tomato fruitripening, and it was postulated that

changes in the degree to which enzymes are bound tomembranes comprise one of the

mechanisms by which the activities of enzymes arecontrolled in tomato pericarp (Mattoo

and Vickery, 1977). Interestingly, the alteration ofcellular membranes results not only in

mixing of cell constituents but also in the loss of cellturgor, making fruits susceptible to

post-harvest handling, transit and marketing (Lara et al.,2015).

Global production of tomato is >100 million tons with a netvalue of over $55 billion,

second only to potato production. Thus, it has drawnresearchers worldwide to understand

mechanisms regulating shelf life of ripe fruit (Fatima etal., 2008; Lin et al., 2014). Ripe

tomato fruits easily damage and deteriorate due to fruitsoftening, mechanical stress during

harvest, handling, transit during transportation andmarketing as well as susceptibility to

various post-harvest decay pathogens (Radzevičius et al.,2009). To reduce post-harvest

losses, tomato fruits are generally harvested at maturegreen stage after the fruit reaches

its maximal size (mature green stage of fruit development)and ripened during transit or at

destination (Triglia, 1998). However, the off-vine ripenedtomato fruit exhibit suboptimal

ripening and generally lack flavour and organolepticattributes (Jeffery et al.,1984; Gupta

et al., 2014). Fruit ripening is a complex, geneticallyregulated temporal process during

which the fruit undergoes major shifts in gene expressionleading to synthesis of a large

number of enzymes involved in fruit ripening (Handa et al.,2014). Although ethylene

regulates a large number of genes during ripening, it doesnot control expression of

many ripening-associated genes, indicating that bothethylene-dependent and ethylene

independent processes determine tomato fruit ripening(Jeffery, 1984; Lincoln et al., 1987;

Barry and Giovannoni, 2007; Handa et al., 2011; Kumar etal., 2014; Kumar and Sharma,

2014; Pech et al., 2012). A coordinate expression ofripening-associated genes is essential

to obtain optimal fruit quality (Brummell, 2006).

Multiple strategies have been used to increase shelf lifeof the tomato fruit, from

approaches using genetics, breeding, molecular techniquesand chemicals to post

harvest management (Mutschler et al., 1992; Gur and Zamir,2004; Rodriguez et al., 2006;

Garg, 2008; Handa et al., 2014). Breeding of new cultivarsby introgression of genetic

components from the wild-type Solanaceae species thatexhibit longer fruit shelf life,

incorporating spontaneous tomato mutations that impair/slowdown the ripening process,

and molecular engineering to modify expression of ripeningassociated genes are examples

for regulating fruit ripening (Pratta et al., 1996; Gur andZamir, 2004; Rodriguez et al.,

2006; Saladié et al., 2007; Handa et al., 2011; Zhu et al.,2014). Irrespective, progress

achieved thus far to extend the shelf life of tomato hasbeen inadequate (No et al., 2007;

Paliyath et al., 2009). The biochemical pathways thatcontribute to fruit ripening and shelf

life include both biosynthesis and catabolic processes,such as cell wall de-polymerizing

enzymes, protein glycosylation, phytohormones, polyaminemetabolism and cuticle

architecture (Carpita and McCann 2000; Brummell andHarpster, 2001; Alexander et al.,

2002; Vrebalov et al., 2002; Giovannoni, 2004; Bargel andNeinhuis, 2005; Srivastava and

Handa, 2005; Negi and Handa, 2008). This list likelyrepresents a tip of the iceberg and

seemingly many more physiological and biochemical processeslikely determine fruit shelf

life and quality attributes. This will come to fruitionthrough coordination of genetics,

biochemistry, molecular engineering and physiologicalprocesses. It is becoming apparent

that both genetic and epigenetic factors play importantroles in determining fruit shelf life

(Seymour et al., 2012; Nath et al., 2014). In this chapter,we discuss various approaches

that have contributed to our understanding of biologicalprocesses regulating tomato fruit

shelf life and the strategies used to improve fruit shelflife.

2 Natural variability

Historically, natural variability has provided a richsource to improve desirable traits in the

cultivated varieties for crops (Vavilov, 1940). The wildrelatives of tomato species have

been the source for several fruit-quality attributes,including thick pericarp, high sugar

levels, pigment accumulation and tolerance to high moistureand wilting (Stevens and

Rick, 1986; Peralta and Spooner, 2006). These wild-typespecies have also provided means

to enhance tolerance and resistance to abiotic and bioticstresses, including salt, drought,

cold, frost, virus, bacteria, fungi, aphid, nematodes andinsects (Peralta and Spooner, 2006).

Such efforts have led to the development of tomatocultivars with increased commercial

performance of fruits, including shelf life (Fulton et al.,2002; Gur and Zamir, 2004;

Spooner et al., 2005; Rodriguez et al., 2006). Genomicanalyses have provided insights

into the history of tomato breeding and allelic variationamong the tomato accessions.

In combination with Genomic Wide Association Study (GWAS),additional targets will be

found to facilitate development of new tomato cultivarswith enhanced fruit shelf life (Ranc

et al., 2012; Lin et al., 2014).

Tomato breeders have exploited natural variation to ingressnovel and desirable

traits into the cultivated tomato varieties (Paran andKnaap, 2007). A genetic cross

between wild-type tomato Solanum lycopersicum L. var.cerasiforme (Dum.) Gray or

S. pimpinellifolium with S. lycopersicum yielded hybridfruits with longer shelf life (Pratta

et al., 1996). However, a divergent-antagonistic selectionwas observed between shelf life

and fruit weight in genetic cross between S. lycopersicumMill. ‘Caimanta’ (short shelf life)

and S. pimpinellifolium (Jusl.) Mill, where the fruitweight but not improved shelf life was

retained during subsequent generations (Rodriguez et al.,2006). Later studies showed

that fruit shelf life was highly influenced by annualenvironmental variation, but progenies

from subsequent generations retained several genomicregions across the years of

evaluation (Pratta et al., 2011). Characterization ofgenetic crosses between a wild-type

cherry (Ce, LA1385 of S. lycopersicum, S. lycopersicum var.cerasiforme) with either an

Argentinean cultivar (Ca, cv ‘Caimanta’) or ripening mutantof S. lycopersicum (nor/nor)

showed that wild-type cherry X normal ripening LA12385yielded best fruit genotype with

improved shelf life and fruit quality (Rodriguez et al.,2010). The QTL analyses of a cross

between S. pimpinellifolium accession LA722 as donor plantand an Argentinean cultivar

Caimanta of S. lycopersicum (CAI) as recurrent parenthighlighted that several loci were

involved in determining fruit shelf life (da Costa et al.,2013). Availability of additional

DNA markers for fruit shelf life should greatly increasethe genetic resources to improve

tomato fruit shelf life. In this regard, the genetic

linkage maps made from crosses between

different tomato species to identify QTLs associated withshelf life, crop productivity and

fruit quality should help accelerate development of newtomato cultivars (da Costa et al.,

2013; Gur and Zamir, 2015; Yamamoto et al., 2016).

3 Ripening mutants

Since fruit shelf life is intimately associated withripening, plant biologists and breeders

have identified ripening-impaired tomato mutants andutilized them to develop long shelf

life tomato cultivars. Although such mutations are notcommon, a few were present in the

available tomato resources. These mutations includeRIPENING INHIBITOR (rin), NON

RIPENING (nor), NEVER RIPE (NR), GREEN RIPE (Gr)/NEVER-RIPE2 (Nr-2), COLOURLESS

NON-RIPENING (CNR), ALCOBACA (ALC), HIGH PIGMENT (hp), DARKGreen (dg),

ATROVIOLACEA (atv), INTENSE PIGMENT (IP), DELAYED FRUITDETERIORATION (DFD)

and a firm-ripe mutant (frm). Also, these mutations (rin,nor, Nr, alc, cnr, frm and DFD) cause

pleiotropic effects and impaired ripening, including lossof climacteric rise in respiration

and ethylene production, reduced fruit softening andpigment accumulation but fruit shelf

life, indeed, extended (Robinson and Tomes, 1968;Tigchelaar et al., 1973; Lobo et al.,

1984; Mutschler, 1984; Kendrick et al., 1994; Thompson etal., 1999; Schuelter et al., 2002;

Barry and Giovannoni, 2006; Levin et al., 2006; Saladié etal., 2007; Garg et al., 2008a,b).

However, in the recessive state, the heterozygous fruitscarrying one copy of several of

these mutations showed intermediate ripening (Tigchelaar etal., 1978a,b; Garg et al.,

2008b; Handa et al., 2011).

The recessive nature of several of these ripeningmutations, especially rin, nor and

alc, have led to the development of their commercialheterozygous hybrids whose fruit

develop acceptable colour for commercialization withsignificantly longer shelf life than

the normal wild-type fruits (Mutschler et al., 1992; Garget al., 2008b; Rodríguez et al.,

2010; Narasimhamurthy et al., 2013; see Table 1). Forexample, rin, alc and nor hybrids

with three Indian commercial tomato varieties ‘Vaibhav’,‘Sankranti’, ‘Pusaruby’ resulted

in fruits with average shelf life of 36, 37 and 35 days,respectively, compared to 17 days

for the parental non-hybrid wild-type fruit. The shelf lifeof hybrid fruits with these three

mutations ranged from 174 to 245% of the wild-type fruits,similar to other studies

(Mutschler et al., 1992; Schuelter et al., 2005; Garg etal., 2008b). Gr and Nr have not been

used in commercial breeding to develop hybrids as thesemutations have deleterious

effects on seed germination, seeding vigour and fruitappearance (Gubrium et al., 2000;

Clevenger et al., 2004; Barry et al., 2005, 2006). Owing todominant nature, cnr mutation

also has not been used to develop longer shelf-lifecultivars (Manning et al., 2006).

The molecular nature of these longer fruit shelf lifeabnormal ripening mutants has been

characterized. The RIN mutation is in a gene that is amember of MADS-box transcription

family and is designated as SlMADS-rin (Vrebalov et al.,2002). The MADS-box transcription

factor family regulates diverse developmental processes inflowering plants, particularly

the molecular architecture during flower morphogenesis (Ngand Yanofsky, 2001;

Vrebalov et al., 2002; Hileman et al., 2006). SlMADSregulates both ethylene-dependent

and ethylene-independent processes during tomato fruitripening and its absence alters

transcriptional pattern of many genes with pleiotropiceffects on many ripening associated

processes, including climacteric respiration, ethyleneproduction, pigment accumulation,

fruit softening and volatile aromatic compounds (Mattoo andVickery, 1977; Vrebalov

et al., 2002; Hileman et al., 2006; Kumar et al., 2012;Fujisawa et al., 2013).

Early studies on the rin function included one in which ringene was shown to prevent

decreases in enzyme activities that occurred during normalripening (Mattoo and Vickery,

1977). These included phosphorylase, pI 5 peroxidase, mostof the esterases except the pI

8.5 isoform, and most of the phosphatases except the pI 4.6isoform. On the other hand,

rin did not prevent the decreases in the total activitiesof peroxidase, IAA oxidase, esterase

of pl 8.5 or the appearance of the pI 8.2 isoform of

peroxidase (Mattoo and Vickery, 1977).

Cnr, a dominant mutation, has been assigned to the upstreamregion of the locus

encoding an SQAMOSA promoter binding (SPB) transcriptionfactor without any

observable change in the coding region of this gene(Manning et al., 2006). These results

have been interpreted as a heritable epigenetic change,which causes hypermethylation of

cytosine located at the upstream of the predictedtranslation start site, resulting in a drastic

reduction in Cnr gene expression (Manning et al., 2006;Zhong et al., 2013). Green-ripe

(Gr) mutation has been implicated in disturbing homeostasisof ethylene signalling,

starting from early fruit development to late ripeningstages (Barry and Giovannoni,

2006). Never-ripe 2 (Nr-2) mutation encompasses a deletionin an ethylene receptor gene

(homologous to AtETR1) impairing ethylene-inducible geneexpression (Yen et al., 1995).

Non-ripening (Nor) mutation is in a gene that is a memberof the NAC domain family

that is an essential transcription factor to regulateripening-associated gene expression

(Moore et al., 2002). Alcobaca (alc) mutation has beenclassified as a nor allele in which

this mutation has altered thymine to adenine at position317 of the coding sequence of

the NAC (Casals et al., 2012). Delayed Fruit Deterioration(DFD) is a relatively new mutant

and appears to be another allele of nor (Rose et al.,2012). The firm ripening tomato

mutant (frm) is suggested to represent an allele oflutescent-2 (l-2) gene that encodes a

zinc metalloprotease (Schuelter et al., 2002; Barry et al.,2012).

4 Molecular determinants

Tomato fruit shelf life is largely limited by excessiveripening-associated fruit softening.

Based on the comparative biochemical genetics of the normalripening versus ripening

impaired tomato mutants, the cell wall and middle lamelladissolution, degradation of

polysaccharides and reduction in the bonding betweenpolysaccharide polymers during Table 1 Effects ofingression of rin, alc and nor mutations on shelf life andfruit yield in commercial tomato varieties (retabulatedfrom Yogendra and Gowda, 2013) Shelf life, days afterripening Genotype Parental rin alc nor 38 44 39(Non-hybrid) Hybrid Sankranti 19 34 35 34 Vaibhav 19 35 4135 Pusaruby 15 35 36 36

tomato fruit ripening have been implicated in fruittextural changes leading to the

softening during ripening (Brummell and Harpster, 2001;Negi and Handa, 2008). The

microscopic and biochemical evidence for the dissolution ofthe middle lamella, reduction

of intercellular adhesion, depolymerization ofpolysaccharides, including solubilization

of hemicellulosic and pectic polysaccharides, providedsupport to these hypotheses

(Redgwell et al., 1997; Brummell and Harpster, 2001; Cantuet al., 2008; Negi and Handa,

2008). Numerous investigations using tools of geneticengineering have been carried out

to determine the role of these components in determiningthe shelf life of ripe tomato fruit

(Giovannoni et al., 1989; Tieman et al., 1994; Thakur etal., 1996a; Brummell and Harpster,

2001; Pech et al., 2005; Nath et al., 2014). Although theseinvestigations supported the

ripening-associated changes in fruit cell wall compositionby degrading several different

types of polysaccharide polymers, they failed to supportthe hypothesis about their role

in determining fruit shelf life. Additionally, severalother factors emerged that play a role

in determining fruit shelf life – change in turgorpressure, membrane breakdown, free

radicals and cuticular waxes (Shepherd and Griffiths, 2006;Prasanna et al., 2007; Vicente

et al., 2007).

5 Role of cell wall proteins

Ripening is associated with a dramatic increase in cellwall degrading enzymes and changes

to hemicellulosic content induced by them (Rose, 1998;Carpita and McCann, 2000;

Prasanna et al., 2007; Negi and Handa., 2008).Solubilization of pectin and breakdown

of xyloglucans have been implicated in tomato fruitsoftening. It has been suggested

that xyloglucan breakdown contributes to the initiation ofsoftening whereas solubilization

of polyuronides contributes to the dissolution of themiddle lamella (Wakabayashi,

2000). The middle lamella is composed of pectin layercemented with Ca 2+ and provides

adhesion in the neighbouring cell to maintain cellularintegrity (Thakur et al., 1996a,b;

Brummell, 2006; Vicente et al., 2007; Negi and Handa,

2008). The ripening-associated

changes in the enzymatic activities of polygalacturonase(PG) (Dellapenna et al., 1986;

Biggs and Handa, 1989), pectin methylesterase (PME)(Harriman et al., 1991), endo

1,4,b-glucanase (Lashbrook et al., 1994), xyloglucan endotransglycosylase (De Silva et

al., 1994; Arrowsmith and De Silva, 1995), b-galactosidase(Smith and Gross, 2000) and

pectate lyase (Marin-Rodriguez et al., 2002) wereconsidered to determine the rate of fruit

softening process. Roles of these enzymes in fruitsoftening and shelf life were discerned

by their transgenic overexpression and/or antisense RNAsilencing. Higher expression of

SlPG had no effect on fruit softening; its antisenseinhibition resulted in slightly firmer fruit

(Giovannoni et al., 1989; Kramer et al., 1992; Langley etal., 1994). Antisense silencing of

SlPME resulting in ~95% reduction in PME activity led todecreased pectin breakdown,

increases in pectin size and methoxylation degree, andjuice viscosity. However, little

effect on fruit texture and softening of SlPME-silencedfruit was seen (Tieman et al., 1992;

Tieman and Handa, 1994; Thakur et al., 1996a,b; Phan etal., 2007). The simultaneous

impairment of multiple SlPME or SlPG and a SlPME also didnot significantly change fruit

texture (Sheehy et al., 1988; Giovannoni et al., 1989;Brummell and Harpster, 2001). The

transgenic fruits with impaired expression of one of theb-galactosidases, b-galactosidase

4, were firmer than the wild type (Smith et al., 2002), butthe reduction in b-galactosidase

1 had no quantifiable effect on fruit firmness (Carey etal., 2001).

Expansin (Exp) is another cell wall–associated proteinimplicated in cell wall–loosening

through the modulation of hemicellulose-celluloseinteractions (Cosgrove, 2005).

Transgenic tomato fruit with reduced expression of SlExp1showed relatively higher fruit

firmness and increased shelf life compared tonon-transgenic parental fruits (Brummell et

al., 1999; Minoia et al., 2016). Increased fruit firmnessand higher juice viscosity in fruits

with simultaneous reduction in the expression of SlPG andSlExp1 were also reported

(Powell et al., 2003). The antisense inhibition of a RabGTPase enzyme also reduced fruit

softening, suggesting an essential role of vesicletrafficking and cell wall deposition in

tomato fruit during ripening (Lu et al., 2001; Lunn et al.,2013). Tunicamycin, an inhibitor of

protein glycosylation, impaired the in vitro ripening oftomato pericarp discs, suggesting

a role of glycosylation in fruit ripening. The geneticevidence for the role of glycosylation

in fruit ripening was provided when the expression ofeither a b-mannosidase or a b-d

N-acetylhexosaminidase, the two enzymes involved inmodifying glycosylation, was

suppressed. This suppression led to 2 to 2.5-fold higherfruit firmness and shelf life

enhancement by about 30 days as compared to the wild-typefruit (Meli et al., 2010).

6 Role of epidermal waxes

Cuticle is the first site of interaction with the outsideenvironment and as such plays

significant roles in many biological processes, includingefficient barrier to water loss and

pathogen entry (Kolattukudy, 1980; Fich et al., 2016).Tomato fruit cuticle is relatively thick

and serves as a continuous extracellular membrane coveringouter epidermis cell walls

and extending into radial and inner tangential walls(Wilson and Sterling, 1976; Bargel and

Neinhuis, 2005; Shepherd and Griffiths, 2006). Thelipophilic waxes covering the cuticles

mainly consist of complex biopolymers of long aliphaticchains with various functional

groups, including fatty acids, alcohols, esters, aldehydesand alkanes intermingled

with triterpenoid and phenolic components (Vogg et al.,2004; Bargel et al., 2006). It

has been suggested that the aliphatic composition of theintra-cuticular wax layers acts

as a primary barrier against transpiration while theepicuticular aliphatics play a minor

role (Vogg et al., 2004; Schreiber, 2006). Cuticlesrestrict transpirational water loss as the

water permeability increases several orders of magnitudeafter wax extraction (Isaacson

et al., 2009; Schreiber, 2010). Structure and layerformation of cutin, and not its amount,

seem important in providing effective barrier to limitwater loss (Hovav et al., 2007; Leide

et al., 2007; Fich et al., 2016). Fruits from acutin-deficient tomato mutant cd2 had a large

reduction in fruit cutin levels with a minimal effect oncuticular transpirational rate, whereas

fruit from cd1 mutant showed a marginal reduction in cutinbut had significantly increased

water permeability (Isaacson et al., 2009).

Fruit from Delayed Fruit Deterioration (dfd) mutant haslonger shelf life, and

characteristically increased cuticular waxes with alteredchemical composition compared

to fruit from a non-isogenic normal ripening Alisa craigcultivar (Saladié et al., 2007). These

authors suggested that the significantly alteredcomposition of circular waxes and reduced

water loss in ripe dfd mutant fruit indirectly increasedtheir shelf life. The biochemical

nature of dfd mutation is yet to be determined, though itis believed to be an allele of

nor (Rose et al., 2012). Biochemical characterization ofthe amount and the type of wax

present on the surface of fruits from rin, nor and Alcobacamutants supports the hypothesis

that cuticular waxes play a role in extending fruit shelflife. The cuticle lipid composition of

mutant fruits differed significantly from the controlfruit, being enriched in C18 monomers

while the total cuticle wax (including fatty acids andalkan-1-ols) was much higher in nor

and rin fruits particularly at the red-ripe stage (Kosma etal., 2010). As mentioned above,

cuticle can be a barrier also against pathogens andtherefore has the potential of reducing

pathogen-associated post-harvest decay and crop loss.Notably therefore, tomato fruit

from dfd mutant with significantly altered composition andamount of waxes was found to

have enhanced resistance to Botrytis cinerea (Isaacson etal., 2009).

7 Hormonal regulation

The involvement of plant hormones in tomato fruitdevelopment and ripening has

been recently summarized (Srivastava and Handa, 2005; Kumaret al., 2014; Kumar and

Sharma, 2014; Nath et al., 2014). Although most planthormones play a role(s) in fruit

development and ripening, involvement of ethylene, thegaseous ripening hormone is

directly associated with both fruit ripening and shelflife. However, the hormone-based

commercial applications to extend post-harvest shelf lifeof tomato fruit, except MCP, are

not yet available.

7.1 Ethylene

Ethylene holds a special place among plant hormones as aregulator of both ripening and

shelf life of climacteric fruits, including tomato (Mattooand Suttle, 1991; Oeller et al., 1991;

Fluhr and Mattoo, 1996; Alexander and Grierson, 2002;Srivastava and Handa, 2005; Barry

and Giovannoni, 2006; Klee et al., 2013; Grierson, 2013;Hoogstrate et al., 2014; Kumar

et al., 2014; Kumar and Sharma, 2014; Nath et al., 2014).The role of ethylene in extending

shelf life of tomato fruits was first hypothesized based onthe lack of ethylene production

in several non-ripening tomato mutants (Tigchelaar et al.,

1973, 1978a,b). That ethylene is

essential in tomato fruit ripening and shelf life wasequivocally first demonstrated when the

critical gene in ethylene biosynthesis,1-aminocyclopropane-1-carboxylate synthase (ACC

synthase) was silenced in transgenic tomato (Oeller et al.,1991). The optimally reduced

ethylene production via this reverse genetics approachresulted in dramatic increase in

shelf life (up to 120 days) of transgenic fruit; theripening could be restored by exogenous

ethylene treatment (Oeller et al., 1991). Elucidation ofethylene biosynthetic perception

and signal transduction pathways have provided several newtargets to develop tomato

fruit cultivars with extended shelf life (Klee et al. 1991;Fluhr and Mattoo, 1996; Xiong

et al., 2003, 2005; Behboodian et al., 2012; Harpaz-Saad etal., 2012; Gupta et al.,

2013). Increased fruit shelf life has been achieved bysilencing of ACC synthase or ACC

oxidase (the terminal enzyme in ethylene biosynthesis), orby silencing both these genes

simultaneously (Xiong et al., 2003, 2005; Behboodian etal., 2012; Gupta et al., 2013;

Sobolev et al., 2014). Overexpression of a bacterial ACCdeaminase resulted in decreased

levels of ACC in fruits, reduced ripening-associatedethylene production, and increased

fruit shelf life (Klee et al., 1991).

The biochemical and genetic characterization of ethylenesignalling pathway has

provided significant insight of the molecular components

regulating ethylene action

(Harpaz-Saad et al., 2012; Shakeel et al., 2013). Briefly,a family of ethylene receptors

act as negative regulators of ethylene signalling pathway.In the absence of ethylene,

a Ser/Thr kinase (CTR1) remains activated and inactivatesEIN2 by phosphorylating it.

EIN2 is an ER-bound protein with similarity to NARPmetal-ion transporters, activated by

proteolysis resulting in the release of its C-terminaldomain and facilitating its migration

to nucleus, thereby relieving the downstream inhibition ofethylene signalling (Shakeel

et al., 2013). In the presence of ethylene, the receptorforms a complex with ethylene,

which inactivates CTR1 and activates EIN2. The activatedEIN2 either directly or indirectly

activates expression of several transcription factorsincluding EIN3 and EIN3-like1 (EIL1).

Although this linear cascade of signalling initiatesethylene response, the mechanism

of ethylene response becomes more complex due to activationof several transcription

factors such as ethylene response factors (ERFs), whichactivate a massive change

in transcriptome (Lee et al., 2012). Ripening tomato fruitexpresses several ethylene

receptors, signalling components and ERFs that provide arich source of targets to modify

ethylene responses. Although functional role of most ofthese transcriptional factors is

not yet understood, it would likely provide tools toimprove fruit shelf life. In regard to

utilizing ethylene signalling pathway genes to alter fruitshelf life, several transgenic fruit

have been developed. Ethylene signalling receptors intomato include ethylene-receptor

proteins (ETR1-7, CTR1-4, ethylene insensitive 2 (EIN1-4),ERS1, ERF1-6 (Zhou et al., 1996;

Kumar and Sharma, 2014). The antisense inhibition of SlERF1increased tomato fruit shelf

life, while overexpression of SlERF1 enhanced ripeningleading to higher carotenoid

accumulation, softening and wrinkling during post-harveststorage of fruits (Li et al., 2007a;

Lee et al., 2012). Pepper SEPALLATA (SEP) gene CaMADS-RINpartially complemented the

rin mutation and altered expression patterns of bothethylene-dependent and ethylene

independent gene transcripts during tomato fruit ripening(Dong et al., 2014). These

transgenic fruits also showed higher ethylene productioncompared to rin fruits and it was

suggested as a novel method to enhance tomato fruit shelflife.

The characterization of the Nr mutation in anethylene-receptor gene, SlETR1, led to

the isolation of its additional alleles Sletr1-1 andSletr1-2 from a mutant library of Micro

Tom (Okabe et al., 2012). The Sletr1-1 mutant allele causedundesirable pleiotropic

effects in tomato hybrids; however, fruits from Sletr-2hybrids ripened normally and fruit

shelf life increased by 4–5 days (Mubarok et al., 2015).The Sletr1-2 mutation increased

fruit firmness and titratable acidity but did not affectfruit size, ethylene production,

respiration rate, total soluble solids and lycopeneaccumulation (Mubarok et al., 2015).

Overexpression of SlAN2, an R2R3-MYB transcription factor,elevated ethylene production

and reduced carotenoids production, and caused early fruitsoftening (Meng et al., 2015).

Loss of function transgenic mutant of FRUITFULL homologsFUL1 and FUL2 impaired

fruit ethylene production by inhibiting ACC synthase andfruits softened independent of

ripening (Shima et al., 2014).

7.2 Abscisic acid (ABA)

ABA and ethylene seem interdependent as regard ripening andsenescence analysed

prior to the era of genomics (Mattoo and Suttle, 1991;Zhang et al., 2015). It does not

therefore come as a surprise that genes regulatingbiosynthesis and catabolism of ABA

play essential functions in tomato fruit ripening. RNAisuppression, under the control

of ripening-associated promoter SlE8, of a gene thatencodes 9-cis-epoxycarotenoid

dioxygenase, SlNCED1, a key enzyme in ABA biosynthesis,caused 20–50% reduction in

ABA levels which was associated with down-regulation ofseveral cell wall catabolic genes,

including SlPG, SlPME, SlTBG, SlXET, SlCels and SlExp (Sunet al., 2012). In spite of higher

ethylene production, these transgenic fruits retainedhigher fruit firmness and pectin during

ripening and showed 2- to 4-fold longer shelf life comparedto the non-transgenic parental

fruit (Sun et al., 2012; Ji et al., 2014). Similarly,suppression of SlCYP707A2, a gene that

encodes ABA 8′-hydroxylase (an enzyme in ABA catabolism),using virus-induced gene

silencing (VIGS) resulted in higher ABA levels intransgenic fruits and their early ripening

(Ji et al., 2014). Interestingly, the deficiency of ABA inthe high-pigment tomato mutant

resulted in increased plastid numbers and lycopene contentin fruit suggesting a role of

this phytohormone in tomato fruit ripening (Galpaz et al.,2008).

7.3 Auxin

Auxin is considered an indispensable regulator of tomatofruit development and ripening.

It stimulates cell expansion during fruit development,inhibits ripening at early stage of fruit

development and accelerates fruit senescence after fullripening of the fruit (Bünger-Kibler

et al., 1983; Manning et al., 1994; El-Sharkawy et al.,2016). However, exogenous application

of auxin caused repression of several carotenoidbiosynthesis genes and impaired

accumulation of lycopene in tomato fruit ripening (Su etal., 2015). Its role in ripening remains

complex. Transgenic tomato fruits expressing a pepper CcGH3gene, which encodes an

auxin biosynthesis enzyme, accelerated fruit ripening ratecompared to wild-type fruit (Liu

et al., 2005); RNAi inhibition of Auxin Response Factor2(SlARF2) gene resulted in ripening

colour defects (never gets full red), increased firmness,longer development time (2–3 days)

from anthesis to breaker stage, and lower total ethyleneproduction compared to control

(Hao et al., 2015). Overexpression of plum auxin receptor(PslTIR1) in tomato resulted in a

shorter fruit shelf life as it increased fruit softeningand weight loss after harvest, suggesting

that auxin accelerated fruit senescence (El-Sharkawy etal., 2016).

7.4 Polyamines

Polyamines (PAs) are ubiquitous biogenic amines implicatedin regulating a myriad of

biological processes, including fruit memory and plantlongevity (Mattoo and Handa, 2008;

Nambeesan et al., 2008; Handa, 2011; Harpaz-Saad et al.,2012; Mattoo et al., 2014). Among

the various polyamines present in tomato, spermidine (Spd)and spermine (Spm) showed

positive correlations with several fruit qualityparameters, whereas putrescine showed negative

correlations with these parameters (Handa and Mattoo,2010). Novel genetic intervention by

the expression of either yeast SAM decarboxylase (SPE2)(Mattoo, 2002; Mehta et al., 2002)

or yeast Spd synthase (SPE3) (Nambeesan et al., 2010) intransgenic tomato lines caused

higher levels of Spd/Spm to accumulate and in the processenhanced tomato fruit quality

including shelf life. Similarly, expression of a mouseornithine decarboxylase gene under the

control of a fruit-specific promoter significantly delayedon planta ripening and prolonged

shelf life (Pandey et al., 2015). Interestingly, geneticintrogression of ethylene-suppressed

transgenic tomatoes with higher-polyamines trait overcamemany unintended effects due to

reduced ethylene on the primary metabolome (Sobolev et al.,2014).

7.5 Other plant hormones

Salicylic acid (SA) and PAs were shown to inhibit thewound-inducible expression of the

critical ethylene biosynthesis gene ACC synthase in tomatofruit (Li et al., 1992). This

observation was utilized (Mehta et al., 2002) to enhancefruit quality and increase shelf

life of tomatoes. Likewise, post-harvest treatment oftomato fruit with gibberellic acid

(GA) and SA enhanced their storage life by about 9 days and5 days, respectively; these

treatments led to significant delay in fruit weight loss,decay, titratable acidity and total

soluble solids (Pila et al., 2010). Levels ofisopentenyladenine, a natural cytokinin, also

increase during ripening but its role in fruit shelf lifehas yet to be examined (Böttcher et al.,

2015). Brassinosteroids (BRs) influence a large number ofplant growth and development

processes but their role in tomato fruit shelf life is alsonot yet investigated. Nonetheless,

the exogenous application of brassinosteroids to tomatopericarp was found to accelerate

their ripening, indicated by increased lycopene levels andethylene production (Vardhini

and Rao, 2002). Fruits from two jasmonic acid(JA)-deficient tomato mutants, spr2 and def1,

had impaired accumulation of lycopene and reducedexpression of lycopene biosynthetic

genes (Liu et al., 2012). JA-insensitive tomato mutantshowed normal ripening but the

seed development was impaired (Li et al., 2004). Atransgenic tomato mutant impaired

in methyl jasmonate production, due to the silencing ofSlLOXB, had firmer texture and

longer shelf life (Kausch et al., 2011). Clearly, the roleof JA in tomato fruit ripening and

storage life remains to be determined (Fan et al., 1998;Almeida et al., 2015).

8 Controlling pathogen-based impairments

Tomato shelf life is often challenged by various plantdiseases in warm and moist areas

with worldwide losses up to 50% harvested crop (Wilson andWisniewski, 1989). Control

of these diseases during both pre-harvest and post-harvestoperations is essential to

avoid devastating loss due to bacterial and fungal diseaseas they decrease in shelf life

and quality of marketable fruits. Tomato is prone to alltypes of biotic stress, including

viral, bacterial, fungal, nematode and insect pests, butbacterial and fungal pathogens

are responsible for majority of post-harvest losses. Thebacterial soft rot is caused by

several bacterial pathogens, but Pectobacterium carotovorumis responsible for the most

post-harvest decay of tomato fruit (Alippi et al., 1997).Other bacterial pathogens that

cause soft rot in tomato include Xanthomonas campestris,Pseudomonas species, Bacillus

species. Lactobacillus species or Leuconostoc speciescauses sour-rot by producing lactic

acid (Bartz et al., 2013). The bacterial pathogens cannotpenetrate directly into the waxy

surface of tomato fruit since they require small woundopening, surface damage or stem

scar to penetrate and gain entry to the inside of fruit.Once inside the fruit, these bacterial

pathogens grow to quorum required to cause disease andproduce copious amounts of

pectinases and other cell wall–degrading enzymes thatmacerate the fruit tissues leading

to disintegration manifested as rot (von Bodman et al.,2003).

Several fungi are responsible for the post-harvest lossesof shelf life and quality of

tomato fruit. These include Alternaria alternata forAlternaria rot (Feng and Zheng, 2007),

Rhizoctonia solani for fruit rot (Strashnov et al., 1985),Rhizopus stolonifer for rhizopus rot

(Bautista-Barios et al., 2008), Geotrichum candidum for thesour-rot (Pitt and Hocking,

2009), Phytophthora capsici or P. parasitica for buckeyerot (Tompkins and Tucker, 1941)

and Sclerotium rolfsii for Sclerotium rot (Strashnov etal., 1985). Colletotrichum coccodes

causes two distinct diseases in tomato: anthracnose on thefruit and black rot in roots

(Dillard, 1989). Like bacterial pathogens, the fungalpathogens also get entry into fruit

tissue by either infecting a wound site or through naturalopening such as stem scar.

Several viruses and nematodes also cause post-harvestlosses (Bartz et al., 2013), but

these are not subject of this review.

Tomato fruit defence mechanism(s) to protect from pathogensvary depending upon

the maturity and ripening stage of the fruit (Alkan et al.,2015). Upon challenge with a

pathogen, the tomato fruit activates expression of variousdefence-related protein

genes, including those that modify processes such asmetabolism, ethylene biosynthesis

and cell death, for survival (Pan et al., 2013). Geneticengineering of tomato has been

used to enhance resistance to abiotic stress in tomatofruit (Kaur et al., 2017). Likewise,

overexpression of several proteins has been shown to reducedevelopment of diseases

in tomato. For example, potato polyphenol oxidase (StPPO)gene was used to impart

resistance to Pseudomonas syringae pv. tomato byaccumulating cytotoxic quinones (Li

and Steffens, 2002); transgenic tomato fruits expressinghevein (HEV1) were less prone to

the fungal pathogen Trichoderma hamatum (Lee and Raikhel,1995).

During post-harvest ripening and senescence, the tomatofruit begins to lose nutrition

support from the plant and the production of antimicrobialsubstances, becoming more

susceptible to pathogens thereof. Handling andtransportation, machinery injury and

temperature change can all decrease resistance of tomatofruit to pathogens. Pathogens are

ubiquitous in the environment, warm and wet atmospherefavouring their growth in many

production areas, including greenhouse, tropical ornon-tropical field during rainy season

(Prusky, 1996; Carlin et al., 2010; Bartz et al., 2013). Tominimize pathogen-induced losses,

appropriate handling and preservation methods with strictsanitation criteria are essential

during the post-harvest management of fruit (US Food andDrug Administration, 1997).

Control of post-harvest losses due to pathogens begins inthe field by implementing

good agricultural practices, especially maintenance ofsanitation throughout the pre

harvest and post-harvest operations (Bartz et al., 2013).These include delaying their

harvest until after the moisture has evaporated off thefruits and plant canopies in order

to avoid mechanical injuries and spread and growth ofpathogens. Sanitation in the fruit

packing house is a must. Also, inactivation of microbespresent on fruit surface within

about 10 seconds of dumping of fruits in the cleaning watertank is desirable to avoid

internalization of microbes (Bartz et al., 2013).

Although significant progress is being made to developfungicide-based methods to

control post-harvest diseases, there is an urgent need fordeveloping biological control

strategy since the usage of fungicide is harmful to theenvironment and can lead to

development of resistance in pathogens (Terry and Joyce,2004; Sharma et al., 2009).

Low temperature provides an effective fungistatic controlof many fungal pathogens, but

it has limited use in tomato since it is a chillingsensitive crop. However, storage at 12°C

can provide extension of tomato fruit shelf life by severaldays (Gharezi, 2012). Heat pre

treatment also inhibits post-harvest decay. This includeshot water dips, hot dry air and

vapour heat. The treatment times can be several days at35°C to 39°C in hot air, or a dip in

hot water at 63°C for less than a minute (Barkai-Golan,1973; Lurie and Pedreschi, 2014).

Ultraviolet-C irradiation (wavelength below 280 nm)reportedly stimulates beneficial

response in tomato, extending shelf life by reducing theexpression of cell wall degrading

enzymes (Barka et al., 2000).

9 Pre-harvest strategies

Pre-harvest cultivation practices that can significantlyinfluence shelf life of ripe tomato

fruit are summarized below. These include cultivarselection, pruning, maturity, irrigation,

fertilizer use, stress management and other strategies(Nigro et al., 2006; Aghofack

Nguemezi et al., 2010; Patanè et al., 2010, 2011;Pérez-Marín et al., 2011; Arah et al.,

2015).

9.1 Irrigation and abiotic stress treatment

Excessive irrigation during cultivation has been reportedto enhance fruit decay and

reduce shelf life (Ehret et al., 2012). However, the soilwater deficit during fruit expansion

and maturity improved fruit firmness, total and solublesolids, and colour, but decreased

yield, fruit size, and even pulp consistency (Patanè etal., 2010, 2011). Moderate pre

harvest abiotic stress can potentially enhance stresstolerance of fruit or vegetative tissue

by regulating stress defence genes, such as heat-stockproteins (PSPs) and chaperones

(Leshem et al., 1996; Wang et al., 2003).Ionizing-irradiation treatment in cherry tomatoes

induced short-term synthesis of ACC synthase and long-termaccumulation of chitinase,

which is known to have an important role in disease defence(Triantaphylides et al., 1994;

Kumar et al., 2004, 2005).

9.2 Fertilizer usage

Plant nutrition including nitrogen, phosphorus, potassium,boron, calcium, magnesium

and potassium greatly influence fruit quality duringdevelopment and ripening, and post

harvest fruit shelf life (Arah et al., 2015). Calciumdeficiency is associated with a large

number of post-harvest disorders. In tomato, calciumdeficiency has been implicated in the

development of blossom end rot (Sams et al., 2003). Foliarspray of Ca 2+ and Mg 2+ delayed

fruit ripening and led to enhancement of shelf life ofred-ripe fruit (Aghofack-Nguemezi et

al., 2010). Irrigation with fertilizers containing Ca 2+and Mg 2+ significantly increased shelf

life of tomato fruit, and this enhancement was attributedto delayed ripening by Ca 2+ and

involvement of Mg 2 + in preventing senescence (Park etal., 2005; Aghofack-Nguemezi

et al., 2010). Increasing K + in fertilizer negativelyinfluences Ca 2+ content in tomato fruit and

shortens fruit shelf life (Paiva et al., 1998;Aghofack-Nguemezi et al., 2010).

9.3 Maturity

Tomato can be harvested at different stages of maturitysuch as mature green, breaker,

turning and fully red ripe. Each stage of ripening has itsown influence on the fruit quality

and shelf life. Tomato fruit harvested at the mature greenstage and ripened during long

distance transportation had the longest shelf life(Moneruzzaman et al., 2009). However,

this practice generally leads to low quality fruit withimpaired organoleptic attributes.

9.4 Cultivar type

Selection of tomato cultivar plays an important role inmarketable fruit quality and storage

under different conditions. Therefore, the cultivarselection decision is critical for post

harvest marketing of ripe tomato fruits. Tomato fruits fromcultivar Roma VF maintained

higher sugar levels and showed lower weight loss thancultivar Marglobe during post

harvest storage (Getinet et al., 2013). Pruning is a veryeffective way to control fruit size

by providing adequate nourishment during fruit development,but its role in shelf life

depends on cultivar selection (Arah et al., 2015).

10 Post-harvest chemical application

10.1 Calcium

Calcium plays a fundamental role in plant membranefluidity, cell wall stabilization, cell

integrity and cohesion of cell walls (Ben-Arie et al.,

1982; Park et al., 2005). There is a long

history for post-harvest application of calcium salts forpreventing decay and enriching

nutrition for fresh fruits and vegetables (Martín-Diana etal., 2007). Treatment with

calcium chloride has been widely used as firming andquality enhancement for tomato or

diced tomatoes (Wills et al., 1979). Other calcium saltssuch as calcium lactate, calcium

propionate and calcium gluconate enhance firmness in tomatoand reduce bitterness

and the residual flavour caused by usage of calciumchloride (Yang and Lawsless, 2003;

Martín-Diana et al., 2007). Overexpression of a H + /cationexchangers (sCAX1) gene from

Arabidopsis increased the intracellular Ca 2+ levels intomato fruit and prolonged shelf life

but this was accompanied by increased blossom end rot (Parket al., 2005). However, the

antisense-based reduction in the expression of afruit-specific pectin methylesterase (PME)

increased apoplastic water soluble Ca 2+ and reducedblossom end rot in the ripening

tomato fruit (de Freitas et al., 2012). Fruits with reducedPME expression greatly enhanced

processing attributes of tomato fruit, including improvedjuice viscosity, but did not alter

fruit texture and softening (Tieman et al., 1992; Tiemanand Handa, 1994; Thakur et al.,

1996a,b).

10.2 Antioxidants

Oxidative stress has been implicated in maintaining andenhancing resistance to disease

during a longer storage period of fruits (Charles et al.,2009). The accumulation of reactive

oxygen species (ROS) is associated with fruit ripening,especially during the over-ripening

stage. The post-harvest application of an antioxidant, suchas benzyladenine and sodium

benzoate, has been reported to extend tomato fruit shelflife, likely by ameliorating ROS

(Bhagwan et al., 2000; Mondal et al., 2004). This is alsoevident in fruits developed for

increased levels of antioxidants and phytonutrients, as wasdone by expressing chalcone

synthase or transcription factors regulating production ofantioxidants including flavonoids

(Muir et al., 2001; Bovy et al., 2002; Butelli et al.,2008; Luo et al., 2008; Zhang et al.,

2014). The ripe transgenic tomato fruit containingseveral-fold higher levels of various

flavonoids had a significant extension of shelf life (Zhanget al., 2015a). Increase in fruit

shelf life was also reported for the non-transgenic purpleskinned Anthocyanin fruit (Aft)

and atroviolacea (atv; Aft/Aft atv/atv) tomato genotypesdeveloped by introgression of

Solanum chilense and S. cheesmaniae into tomato (Povero etal., 2011; Bassolino et al.,

2013; Zhang et al., 2013). The high anthocyanin fruitdeveloped either by expressing

transcription factors Del/Ros1 or by genetic introgressionhad reduced susceptibility to

Botrytis cinerea, which is a post-harvest pathogen (Zhanget al., 2013). Similar results were

obtained for fruits expressing AtMYB12, a transcription

factor, under the control of a fruit

specific promoter SlE8 and it caused high-levelaccumulation of flavonols in tomato fruit,

the red fruit of which had an orange phenotype (Luo et al.,2008; Zhang et al., 2015a,b).

The AtMYB12- fruits had increased shelf life but were notenhanced as far as tolerance to

B. cinerea was concerned, suggesting differential roles ofdifferent antioxidants in biotic

stress tolerance versus fruit shelf life (Zhang et al.,2015a,b).

10.3 Ethylene action inhibitor, 1-MCP

A cyclopropane derivative, 1-methylcyclopropene (1-MCP), isused as a synthetic

plant growth regulator to inhibit ethylene-induced ripeningand senescence in many

horticultural crops (Blankenship et al., 2003). 1-MCPshares some structural feature with

ethylene and binds tightly to ethylene receptors to blockethylene action and reduces

its deleterious effects in plants (Sisler et al., 1997).1-MCP has been approved by the

Environmental Protection Agency (EPA) for use onhorticultural crops, including floriculture

and ornamental products, and on edible food products. 1-MCPis now approved in over

40 countries to reduce deleterious effects of ethylene onfruit shelf life. In tomato, 1-MCP

prevents decay and weight loss without significantlyinfluencing total soluble solids (TSS)

(Boggala et al., 2015). The commercial usage of 1-MCP inpost-harvest management is

acceptable, as it does not harm the environment and

provides a rapid response, even

when applied at low concentrations for short time.

11 Post-harvest management

Post-harvest management plays an essential role inmaintaining quality and extending the

shelf life of fruits. It is important to manage severalfactors such as temperature, humidity and

gas composition during storage of fruits (Arah et al.,2015). Tomato fruit has a relatively short

shelf life after the onset of ripening. Therefore, it isnecessary to use proper post-harvest

management strategies for slowing down variousphysiological and biochemical processes,

in particular ethylene production and action (Javanmardiand Kubota, 2006; Beckles, 2012).

11.1 Temperature control

Rates of most biochemical reactions are directly linkedwith environmental temperature and

generally these rates increase with increasingtemperatures. The optimum temperature for

ripe tomato fruit is around 20°C, but at this temperaturefruit has a relatively short shelf life

(Kader, 1986), mature green tomato can be kept relativelylonger when stored at 10–15°C

(Castro et al., 2005). The increase in temperature duringpost-harvest storage increases the

rates of respiration and ethylene production along withmany other metabolic processes

and results in lowering fruit shelf life (Hardenburg etal., 1986). Temperature management

is considered one of the most effective methods to maintainfruit quality and increase

shelf life during the post-harvest period (Moneruzzaman etal., 2009). Although shelf life of

many fruits increases with a reduction in temperature,tomato fruit develops physiological

disorders if stored below 8–13°C for an extended period(Raison and Lyons, 1986). The

daytime temperature at harvest also affects fruit shelflife, as the field heat stored within

the fruit at the harvest time would hasten ripening processleading to excessive water loss

and shrivelling of fruits. Short-time pre-cooling(typically to around 12.5°C for tomato fruit)

for rapidly removing field heat was able to reducedeteriorative and senescence effects

during storage efficiently (Brosnan et al., 2001).

11.2 Humidity control

Tomato fruit being rich in water content is prone to rapidwater loss and shrivelling if stored

in a dry place or under inadequate water vapour pressure.Fruits stored at high relative

humidity (RH) maintain other quality attributes, includingnutritional quality, appearance,

weight and flavour (Tigist et al., 2013). Managing watervapour pressure (RH) is essential

to reduce water loss and maintain fruit quality. Maturegreen tomato is best stored within

85–95% RH (Castro et al., 2005), and for firmer ripeningwithin 90–95% RH (Suslow and

Cantwell, 2009). However, 100% RH should be avoided toprevent mould and fungal

growth during storage (Moneruzzaman et al., 2009).

11.3 Modified atmosphere packaging (MAP)

Air composition during storage of fresh produce greatlyalters various physiological and

biochemical processes and impacts their freshness andstorage life. It has led to MAP

being widely used for extending the shelf life of freshproduce by removing or changing

the air component and moisture levels during storage insitu with desirable permeability

for oxygen, carbon dioxide and water vapours (Kader et al.,1989). MAP benefits produce

shelf life by delaying over-ripening, respiration, ethyleneproduction and water loss

(Beaudry et al., 1992; Petracek et al., 2002). For tomatofruit, the optimum gas composition

to maintain fruit quality of unripe green fruit is 3–5% O 2but is variable for CO 2 . Mature

green fruits are best stored at 1–3% CO 2 dioxide whereasthe ripe fruit can be stored at

1–5% CO 2 (Sandhya, 2010).

12 Conclusion and future trends

Post-harvest deterioration of tomato fruit crop is one ofthe major challenges to the

tomato industry, as it leads to a huge economic loss atevery step of the marketing chain,

especially during long distance shipping/transportation.This chapter discusses various

strategies that have been utilized to extend tomato fruitshelf life. Natural variation and

availability of non-ripening mutants have provided means todevelop tomato cultivars

with enhanced shelf life. However, quality of fruit ofthese cultivars is inadequate in

terms of the quality organoleptic taste attributes. Thus,

the need to develop tomato

cultivars with both improved organoleptic quality andextended fruit shelf life continues

to be a high priority (Arah et al., 2015). Molecularbreeding and genetic engineering

approaches, especially genome editing, have provided newsets of technologies and

tools that should allow molecular dissection of therelationship between shelf life and

fruit quality. Transgenic fruits with variously enhancedattributes have been genetically

developed by overexpressing or suppressing expression of aselected gene(s) and/or

regulating a transcription factor(s). An important aspectof fruit quality and its relevance

to the well-being of consumers is the fact that byincreasing the levels of antioxidants,

phytonutrients and other elixirs in fruits along with shelflife, raises hope in the horizon

for enhancing human health quality and containing disease,in addition to increasing

marketing prowess for the economic benefit of the farmer,producer and supplier.

Understanding the fundamental mechanisms of how planthormones work, ethylene in

particular for fruits, will provide new road maps forfuture development of long shelf life

fruits, and override the inadequacy of attributes notbeneficial to human taste and health.

The emerging fundamental information from various facets ofresearch will provide new

ways to maintain desirable tomato fruit quality andovercome the deleterious effect of

senescence to enrich the horticulture industry.


Several excellent articles are available that discussvarious factors that regulate various

aspects of tomato fruit ripening and extend the overallquality including shelf life of fruits

(Mutschler et al., 1992; Rodriguez et al., 2010; Handa etal., 2011; Klee and Tieman,

2012; Seymour et al., 2012; Arah et al., 2015; Tohge andFernie 2015). A recent book

(Fruit Ripening – Physiology, Signalling and Genomics) hasbeen devoted to fruit ripening

(Nath et al., 2014). One resource includes several internetsites, particularly of various

universities that provide information on maintaining theshelf life of tomato fruits. Here we

have synthesized information from a lot of literature ontomato fruit shelf life.

14 Acknowledgements

KW is partially supported by a fellowship through the ChinaScholarship Council

and Purdue Agricultural Research Program. AKH research issupported by a Hatch

(IND011872H) project and USDA/NIFA 2012-67017-30159. Tradenames or commercial

products mentioned in this publication are only to providespecific information and do not

imply any recommendation or endorsement by the authors.USDA is an equal opportunity

provider and employer.

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13 Chapter 13 Insect-transmitted viraldiseases infecting tomato crops

1 Introduction

The major insect-transmitted viruses infecting tomato aredescribed in this chapter. A

handful of minor viruses are also mentioned.

Many viruses transmitted by insects cause great harm totomato crops in the field and

in the greenhouse, seriously damaging tomato production inmany regions of the globe.

The most important virus vectors are the aphids(Aphididae), whiteflies (Aleyrodidae),

thrips (Thysanoptera) and leafhoppers (Cicadellidae)(Nault, 1997). A particular virus

is transmitted by one vector type only. Some tomato virusescan also be transmitted

mechanically from infected to healthy plants, by humanactivity and in some cases by

pollinating insects.

All the major viruses infecting tomato plants aretransmitted naturally during feeding of

the insect vectors on the leaf vascular tissues accordingto acquisition and transmission

patterns specific to the virus-vector complex (Fereres etal., 2015; Whitfield et al., 2015).

Following inoculation, the viruses generally replicate inthe phloem-associated cells,

sometimes in the parenchymal cells. They move cell-to-celland long distance until they

infect the host plants systemically.

Tomato spotted wilt virus (TSWV) is vectored by the thrips(Frankliniella occidentalis) and

is persistent. The immatures, which do not move amongplants, acquire the virus. Then, it

replicates within the gut. The virus is transmitted byolder larvae and adults.

Begomoviruses are transmitted by the adult whitefly(Bemisia tabaci) in a circulative and

propagative fashion. Once acquired, viral particles movealong the digestive tract, pass

into the haemolymph and from there to the salivary gland, aprocess that takes about 24

hours. The insects are able to transmit begomoviruses fortheir entire life. The whitefly

transmitted closteroviruses and criniviruses reach only theforegut of the vector and are

transmitted in a semi-persistent manner. These viruses areretained in the vector for about

3–9 days are not passed through the egg.

Leafhopper and aphid-vectored viruses are non-persistent.The viruses are picked up

on the insect’s mouthparts within a few seconds of feedingon an infected plant, and

transmitted to a new plant by winged adults duringsubsequent feeding. The viruses do

not replicate in the insect’s body.

Increased insecticide resistance, global warming, changingof agricultural practices

and increasing global trade of plant materials are allfactors enhancing the appearance

and spread of insect-transmitted viruses (Gilbertson etal., 2015). Management of insect

transmitted tomato viruses is a long-lasting race betweenthe emergence of new viruses

coupled with the proliferation of quickly adapting vectors

and strategies that include

physical and chemical protection from insects anddevelopment of virus-tolerant crops.

Nowadays, genetics and genomics offer a panoply of toolsthat are improving the

diagnosis of viruses in infected tomatoes and in vectors,facilitate the identification and

introgression of virus-resistance genes into cultivars andallow the precise modification of

the genome of viruses, plants and insects. The sequencingof large numbers of wild tomato

species and cultivated lines and of the major insectvectors opens the way to identify

genes involved in virus transmission and in virusresistance, which could be used by tomato

geneticists and breeders to improve tomato protectionagainst viruses and their vectors.

2 Viruses transmitted by aphids

2.1 Cucumber mosaic virus

2.1.1 Epidemiology and symptoms

Aphids are able to transmit over 300 plant viruses,including Cucumber mosaic virus (CMV)

and about 100 different members of the Potato virus Y (PVY)group. CMV has an extensive

host range. It may infect more than 750 plant species,including many vegetables, weeds

and ornamentals. CMV can occur wherever tomatoes are grown.CMV tomato-specific

strains have been reported.

Tomatoes infected with CMV are often stunted and bushy, andmay have distorted

filiform leaves with green-yellow mosaic patterns. Severely

affected plants produce few

small fruits. CMV is not transmitted by handling infectedplants and is not seedborne.

2.1.2 The virus

CMV belongs to the family Bromoviridae (genus Cucumovirus).CMV has a linear positive

sense single-stranded (SS) RNA genome composed of threecomponents of 3.389 kb, 3.035

kb and 2.197 kb, each packaged in a separate isometricparticle. RNA 1 and 2 encode

the 1a and 2a proteins, respectively, which constitute twosubunits of the virus replicase

complex. RNA 2 also encodes the 2b protein that is involvedin host specificity, long

distance movement, symptom induction and suppression ofgene silencing. RNA 3 encodes

two proteins: 3a, a cell-to-cell movement protein (MP), and3b, the capsid protein (CP). CP is

involved in cell-to-cell movement, virion assembly andaphid-mediated transmission (Nouri

et al., 2014). Some CMV strains contain the CMV associatedRNA 5 (CARNA-5) involved in

the expression of necrotic symptoms on fruits (Fig. 1)(White et al., 1995).

2.1.3 Transmission by aphids

Aphids usually infect cultivated tomatoes after they haveacquired the virus from a wild

host during feeding. The virus is not seedborne in tomato.More than 60 aphid species,

including the green peach aphid (Myzus persicae), arecapable of transmitting the virus

in the typical stylet-borne non-persistent manner. In sucha case, the virus is assisted in

its transmission by a specific configuration of its coatprotein and by a non-structural

virus-encoded protein that interacts with the aphid-virusretention binding site and forms

a bridge between the virus and the aphid stylet. CMV isacquired by the aphid within

one minute of feeding on an infected plant. The aphid isthen able to transmit the virus

immediately; the ability to transmit the virus quicklydeclines and is lost within several

hours. The virus does not translocate into the insecthaemolymph. Transmission efficiency

varies with aphid species, virus strain, host plantspecies, environmental conditions, and

time of the year (Gildow et al., 2008).

2.1.4 Resistance to CMV in tomato

CMV is difficult to control because of its extremely broadnatural host range. There are

no good sources of genetic resistance to CMV (neither forPVY nor for Tobacco etch virus

Figure 1 Tomato plants in a greenhouse infected withCucumber mosaic virus (CARNA 5) (photography:

A. Koren).

(TEV)) available in commercial tomato cultivars. Effortsusing traditional breeding for CMV

resistance have mostly been unsuccessful. Therefore,control strategies may include early

planting of tomatoes and peppers, eradication of weeds inand around fields, use of

reflective mulches to repel aphids and application ofinsecticide when needed.

CMV-resistant transgenic tomato plants have been achieved

with the help of genetic

engineering. In addition, the potential of gene silencingand modulating plant defences

has been shown to be feasible. Partial resistance wasachieved by expressing a defective

viral replicase gene in transgenic tomato (Gal-On et al.,1998). Resistance was also achieved

by expressing an RNAi construct directed against a CMV-Oreplicase gene in transgenic

tomato plants (Ntui et al., 2014). Transgenic plantsinoculated with CMV strains O and Y

were symptomless or presented light symptoms. Theresistance was correlated with post

transcriptional gene silencing (PTGS). Another approachmight be promising as well. It

was recently shown that Arabidopsis plants (ecotype Col-0)infected with the CMV strain

Fny produced the aphid feeding-deterrent4-methoxy-indol-3-yl-methylglucosinolate

(4MI3M) in the phloem (Westwood et al., 2013). The CMV 2aprotein (an RNA-dependent

RNA polymerase [RdRp]), which enhances plant defences, wasinvolved in the increase of

4MI3M accumulation. The observed phenomenon was CMVstrain-specific because LS

strain of CMV did not induce feeding deterrence inArabidopsis ecotype Col-0.

2.2 Potato virus Y

2.2.1 Epidemiology and symptoms

PVY is a member of the family Potyviridae. It occursworldwide but has a narrow host

range, affecting plants in the Solanaceae family (tomatoes,potatoes and peppers). It is

transmitted by aphids. PVY can destroy the entire tomatocrop if infection starts early

during the growing season and if high aphid populations arepresent.

Symptoms on tomato vary according to the strain of PVY,plant age, varieties infected

and environmental conditions. Severe symptoms include brownnecrotic areas on mature

leaflets. In many cases, all leaflets are affected. Leavesformed after the onset of PVY

exhibit mild wrinkling, slight distortion and mildmottling. Leaflets of plants infected for a

long time are rolled downward with curved petioles. Stemsoften show brown streaking

but the fruits are symptomless. Mature plants are stuntedand yield is reduced (Fig. 2). A

necrotic strain of PVY was characterized from tomato; itdid not infect potato and pepper;

its sequence was quite remote from that of potato PVY(Rosner et al., 2000). Tomato plants

are often co-infected with CMV and PVY. In this casesymptoms are very severe as if the

plant was infected by another third virus and the infectedtomato plants do not yield at all.

2.2.2 The virus

The virion appears as a non-enveloped rod shaped flexuousparticle, 680–900 nm long

and 11–20 nm in diameter. The nucleocapsid contains about2000 copies of the CP. PVY

has a SS positive sense RNA genome of about 9700nucleotides with a single open reading

frame, which can act as an mRNA (Jakab et al., 1997). The5’-end of the viral genome is

covalently linked to the viral encoded VPg protein. The 3’end is constituted by a poly

adenylated sequence. The PVY genome encodes a polyprotein(3063 residues) cleaved

by three viral protease (P1, HC-Pro and Nib) to producenine functional proteins (from N

to C terminus: P1, HC-Pro, P3, 6k1, CI, 6k2, NIa, NIb andCP). P1 is a protease; HC-Pro is

involved in aphid transmission and has movement, proteaseand gene silencing functions;

P3 is a replicase; CI is a helicase; VPg is a protease; Nibis an RdRp; CP is the coat protein;

6k1 is a pathogenicity factor and 6k2 is involved in thereplication complex (Lorenzen et

al., 2006). These viral proteins are involved in differentsteps of the viral cycle.

2.2.3 Vector transmission

The green peach aphid (Myzus persicae) is the mosteffective PVY vector, but other aphid

species are also good vectors (Boquel et al., 2011). PVY istransmitted in the non-persistent

non-circulative manner by many aphid species. Aphids canacquire the virus in less than

one minute from an infected plant and transmit it to ahealthy plant in less than one minute.

The virus may be retained by non-feeding aphids for longerthan 24 hours (Fereres and

Raccah, 2015). PVY can also be transmitted mechanically.Potato is an important source of

the virus for tomato. Seed transmission of the virus hasnot been reported.

2.3 Minor viruses transmitted to tomato by aphids

2.3.1 Tobacco etch virus

TEV is a typical potyvirus (genus Potyvirus, familyPotyviridae), which infects tomatoes and

other plants in the Solanaceae family. TEV is foundprimarily in the Americas, including

Canada, the United States, Mexico and Venezuela. The genomeof TEV is similar to that

of PVY (Hari, 1981). TEV is transmitted in a non-persistentmanner by at least 10 species

of aphids, including M. persicae. TEV can be easilytransmitted mechanically; seed

transmission has not been reported.

The occurrence of TEV in tomato fields is closelyassociated with other infected

solanaceous crops, especially pepper and natural weedhosts, which serve as virus

reservoirs. Leaves of infected plants are severely mottled,crumpled and wrinkled. Plants

infected at an early age are severely stunted. The youngerthe plants are when infected,

the greater the reduction in yield. Fruits from infectedplants are mottled and do not

achieve marketable size.

Because of the lack of TEV (and PVY) resistance in tomato(wild and cultivated) and

because both viruses are transmitted by aphids in anon-persistent manner, most control

measures consist in the removal of solanaceous weedreservoirs and in the protection of

plants with nets.

2.3.2 Potato leafroll virus

Potato leafroll virus (PLRV) is more commonly associated

with potato, but a tomato

specialized isolate of PLRV has been identified in New Yorkand Florida. PLRV is vectored

by aphids in a persistent manner. The virus is a member ofthe genus Polerovirus. Leaf

rolling and marginal leaf chlorosis are the typical foliarsymptoms seen. Aphid control

should reduce the amount of virus spread.

2.3.3 Tobacco mosaic virus

Tobacco mosaic virus (TMV) or tomato mosaic virus (ToMV) isnot vectored and spread

through feeding by insects commonly occurring in thegreenhouse or field. In most cases,

the virus is transmitted mechanically during plant handlingby farmers. In some cases,

aphids can transmit TMV mechanically. Insects that walk oninfected leaves can pick up

TMV particles on their legs, fly to new plants, andinoculate these plants with TMV while

moving on their foliage (Harris and Bradley, 1973).

3 Transmission by thrips: tomato spotted wilt virus

3.1 Agricultural importance and epidemiology

TSWV (genus Tospovirus; family Bunyaviridae) causes one ofthe most common virus

diseases of tomatoes grown in greenhouses (Scholthof etal., 2011). It is transmitted by

the thrips Frankliniella occidentalis (Thysanoptera:Thripidae). TSWV was first detected in

Australia in 1915 and rapidly spread to other tropical andsubtropical areas worldwide.

The virus infects about 800 plant species. It has become amajor pest for tomato growers

because the thrips vector spreads over long distances bywind and feeds on a large

number of plants, including food crops (such aswatermelons, peanuts and tomatoes) and

ornamentals (lily, impatiens, chrysanthemum and iris)(Pappu et al., 2009). Two emerging

Figure 2 Tomato plants in a greenhouse infected with Potatovirus Y (photography: A. Koren).

tospoviruses closely related to TSWV, Tomato chlorotic spotvirus (TCSV) and Groundnut

ringspot virus (GRSV), cause damages to the tomato growersin the Americas (Webster

et al., 2015).

TSWV-infected tomato plants present symptoms that includebrown-spotted leaves,

streaking of stems, and stunted growth (Fig. 3). Ripefruits have a deformed shape and

may be covered with red and yellow rings (Fig. 3), reducingfruit quality and yield. Disease

control (Sherwood et al., 2009) is an uneasy task becauseweeds growing in the vicinity of

greenhouses and fields may constitute virus sources allyear around. If the disease appears,

infected plants should be removed and destroyed. This isnot always effective as the virus

has spread before the appearance of symptoms. Controllingthrips with insecticides is

not effective either because immatures and adults hide instem cracks, leaves and flower

buds. In addition, the insects quickly develop resistanceto common chemicals (Gao

et al., 2012). In greenhouses, covering entries with finemesh clothes may reduce thrips

entry. Yellow sticky cards allow monitoring and earlydetection of the presence of thrips,

increasing chances of removing infected plants before thedisease has spread. Quick

TSWV serological and molecular detection tests arecommercially available.

3.2 The virus

TSWV has a SS RNA genome with negative polarity ((-)ssRNAviruses). The genome is linear

and is 17.2 kb in size and comprises three segments termedS (2.9 kb), M (5.4 kb) and L

(8.9 kb) (Tsompana et al., 2005). The three genomic RNAsare individually encapsidated.

TSWV virions are spherical in shape with a diameter of80–110 nm. The L RNA codes for

the RdRp. The M RNA encodes precursors for two structuralglycoproteins, GN and GC,

and a non-structural protein, NSm. The S RNA codes for thenucleocapsid protein (N)

and another non-structural (NS) protein. The three genomicRNAs are tightly linked with

the N protein forming ribonucleoproteins (RNPs). These RNPsare encased within a lipid

envelope consisting of two virus-encoded glycoproteins anda host-derived membrane.

RdRp is needed for replication; GN and GC are dispersedthroughout the surface of the

viral envelope and may be involved in the recognition ofinsect receptors. NSm forms

tubules that facilitate the virus movement in plantscell-to-cell via the plasmodesmata. NSs

crystalline structures are produced in infected insect andplant cells. The NSs protein has

RNA silencing the suppressor activity, and may play a rolein PTGS.

Figure 3 Tomato spotted wilt virus in the open field; left:stunting and brown patches on leaves and

right: severe symptoms (photographs: A. Koren).

3.3 TSWV – thrips – tomato relationship

Spotted wilt is caused by thrips that feed on a variety ofinfected plants by puncturing the

leaves and sucking the content (Whitfield et al., 2005).Thrips deposit their eggs (about

75 per female) into plant tissue and the eggs hatch after2–3 days. There are two feeding

larval stages that are followed by two non-feeding pupalstages. Adults develop from

eggs during the next 20–30 days from egg to adult,depending on the temperature, and

may live for up to three weeks. TSWV must be acquired bythrips during the larval stage

of their development to be transmitted. Larvae sometimesacquire the virus after feeding

on a diseased plant for as little as 5 minutes, but usuallythey must feed for more than an

hour both in acquiring and in inoculating the virus. Onceacquired by the larvae, the virus

persists from larval to adult stages. There is a latentperiod of 3–4 days before the larvae

can transmit the virus. Once acquired by larvae, TSWV isuptaken by the midgut, facilitated

by the viral glycoproteins (GPs). The virus then moves toother cells and organs, such as

digestive tract, muscle system and salivary glands, andbecomes systemically established

in the thrips. Eventually, the virus enters the salivaryglands and is excreted with the saliva

into host plants during thrips feeding. The virus is passedfrom the larvae to the adults,

which can transmit it for the rest of their lives.

TSWV replicates in the midgut and salivary glands of F.occidentalis but is not transmitted

transovarially to the next generation. There is no obviouspathogenic effect of TSWV on

the thrips host. However, proteomic analyses indicated thata number of insect proteins are

significantly altered in response to TSWV, includingproteins associated with the infection

cycle and with antiviral defence responses (Badillo-Vargaset al., 2012).

3.4 Genetic resistance to TSWV and thrips in tomato

Use of host resistance appears to be the best way tocontrol the disease (Riley et al., 2011).

So far, several genes providing various levels ofresistance to TSWV have been identified

(Sw1a, Sw1b, sw2, sw3, sw4, Sw-5, Sw-6 and Sw-7). Some arerecessive (sw2, sw3 and sw4)

and others are dominant (Sw1a and Sw1b). Sw-5 is the mostbroadly used resistance gene.

First identified in Solanum peruvianum, it has providedstable resistance against TSWV

isolates from different geographical locations (Soler etal., 2003). Sw-5 was mapped near a

telomeric region of chromosome 9; five alleles wereidentified and cloned (Sw5-a, Sw5-b,

Sw5-c, Sw5-d and Sw5-e) (Brommonschenkel and Tanksley,1997). Among them, Sw5-b

is the functional allele for conferring resistance to TSWV;

it encodes a 1246 amino acid

protein member of the coiled-coil, nucleotide-binding-ARC,leucine-rich repeat group

of resistance gene candidates. (Spassova et al., 2001). Incertain regions like Brazil, the

pressure of TSWV is so high that plants without theSw-5-resistant gene will not yield at all.

TSWV variants that break the resistance conferred by Sw-5have been described (Aramburu

and Marti, 2003). Unpublished information indicates thatthe resistance provided by Sw-5

can be overwhelmed at high temperatures. Gene silencing andRNAi methods may offer

new solutions for the control of thrips and other insectsin the near future (Badillo-Vargas

et al., 2015).

3.5 New thrips-transmitted viruses

Thrips populations have greatly increased over the past fewdecades, thanks to climate

changes and insecticide resistance, facilitating theemergence of new thrips-transmitted

viruses (Rojas and Gilbertson, 2008). In 2005, adevastating new disease was observed in

tomato and chilli pepper crops in Yunnan, China. Completenucleotide sequences of the

three RNA fragments indicated that the virus was a newmember of the Asian group of

Tospovirus spp., and was termed Tomato zonate spot virus(Dong et al., 2008).

4 Transmission of Begomoviruses by the tobacco whitefly(Bemisia tabaci)

4.1 Plant viruses transmitted by whitefly species

Only a few species of whiteflies transmit viruses, mostlyin the tropics and subtropics, but

the viruses they transmit cause very severe diseases.Whiteflies produce many generations

in a year and reach high populations. Begomoviruses aretransmitted by the whitefly

(Bemisia tabaci) (Hemiptera: Aleyrodidae) in a persistentcirculative manner for all their

adult life time. The criniviruses and thewhitefly-transmitted closteroviruses are vectored

by the whiteflies Trialeuroides vaporariorum, T.abutilonea, and B. tabaci (Navas-Castillo

et al., 2011). The whitefly-transmitted closteroviruses andcriniviruses reach only the

foregut of the vector and are transmitted in thesemi-persistent manner. These viruses are

retained in the vector for about 3–9 days and are notpassed through the egg.

4.2 B. tabaci: a cryptic species complex

B. tabaci is considered as a species complex (or biotypes),with individuals differing in their

host range, resistance to chemicals and ability to transmitbegomoviruses (Brown et al.,

1995). In the 1990s, esterase polymorphism was used toclassify the B. tabaci populations

into biotypes (named after their esterase profile). Thisanalysis showed, for example, that

in the United States, the indigenous A biotype wasdisplaced by an invasive B biotype.

Today, nuclear and mitochondrial DNA sequences are used todiscriminate between

B. tabaci populations and to study their movementworldwide. Accordingly, close to

forty B. tabaci species have been delimited, among them,the most important biotypes

worldwide B and Q, recently termed as MEAM1 and MED,respectively (Boykin et al.,

2013; Wang et al., 2014). Comparative studies on whiteflybiotypes/cryptic species and

the begomoviruses they transmit indicate that begomovirusesand their whitefly vector are

grouped together according to their geographic origin(Brown, 2007).

4.3 The whitefly life cycle

The life cycles of B. tabaci and T. vaporariorum aresimilar, although the two species prefer

different temperature ranges for optimal development:25°C–30°C for B. tabaci and

20°C–25°C for T. vaporariorum. B. tabaci females produceabout 400 eggs during their

lifetime. Eggs are usually laid on the underside of leaves.Eggs hatch in 8–10 days. There

are four immature or nymphal stages. Crawlers or firstinstar nymphs move a short distance

before settling to feed. Second and third instar nymphs arestationary until developing

into the pupal stage from which emerge fully developedadults. Viruses are spread by

adults, which may live for up to 4–5 weeks (Walker et al.,2010).

B. tabaci and T. vaporariorum have a wide range of hostplants among crops,

weeds and ornamental plants. They damage plants by suckingthe plant’s sap causing

reduced growth, stunting and yield reduction. Honeydewsecretions from whitefly can

result in the development of sooty mould on the crop,reducing quality and yield of

the crop.

4.4 Tomato yellow leaf curl and other related Begomoviruses

Tomato yellow leaf curl virus (TYLCV) causes one of themost devastating diseases of

tomato worldwide (Czosnek, 2007). In the field, inoculationcan occur immediately after

transplantation. Infected seedlings will remain stunted andwill not yield fruits (Fig. 4). In

the greenhouse, symptomatic plants are usually found in thevicinity of doors or ventilation

(Fig. 4).

TYLCV (genus Begomovirus, family Geminiviridae) istransmitted exclusively by the

whitefly B. tabaci. The virus possesses a single genomiccomponent (monopartite)

encapsidated in an approximately 20 nm by 30 nm twinnedparticle (Navot et al., 1991).

Its circular SS DNA genome of about 2800 nucleotides isenveloped in a capsid consisting

of two joined incomplete icosahedra of 22 capsomeres, eachcontaining five units of a

260-amino-acid CP (30.3 kDa). The ssDNA TYLCV genomeencodes two genes: the CP

and V2, which has functions of an MP and of suppressor ofRNA silencing. The genome

complementary strand encodes four genes: areplication-associated protein (Rep), a

transcriptional activator protein (TrAP), a replicationenhancer protein (REn), and a symptom

and movement determinant (Díaz-Pendón et al., 2010). Theviral DNA replicates in the

nuclei of infected cells according to a rolling circlemechanism, using its own encoded

proteins and the host cell machinery.

TYLCV comprises a complex of begomoviruses that includesseveral species (delimited

by 89% or less nucleotide identity in the DNA-A likegenome); some of the most common

ones include TYLCV, Tomato yellow leaf curl virus-Mild(TYLCV-Mild), Tomato yellow leaf

curl China virus (TYLCCNV), Tomato yellow leaf curl Malagavirus (TYLCMalV), Tomato

yellow leaf curl Sardinia virus (TYLCSV), Tomato yellowleaf curl Thailand virus (TYLCTHV)

and Tomato yellow leaf curl Vietnam virus (Brown et al.,2014). In contrast to other TYLCV

species and isolates, a TYLCV species from Thailand,TYLCTHV, is a bipartite begomovirus

(Tsai et al., 2011). It is interesting to note thatTYLCVTHV DNA-A is sufficient to produce

Figure 4 Tomato yellow leaf curl virus in the open field(left) and in the greenhouse (right) (photographs,

respectively: F. Vidavski and H. Czosnek).

infection, although symptom appearance is delayed.Recombination between viruses/

strains may be a major driver of TYLCV diversification(Urbino et al., 2013).

Sporadic in the early 1960s, TYLCV has quickly spread fromthe Eastern Mediterranean

Basin to the Middle East, Central Asia, North and WestAfrica, southeastern Europe, the

Caribbean islands, South-eastern United States, Mexico, theSouthern Indian Ocean

islands and Japan (Lefeuvre et al., 2010). Infected plantsare stunted and cease to develop.

Leaflets are stiffened, rolled upwards and with yellowedges. Yield and fruit quality are

greatly reduced. In severely affected regions, crops may beentirely lost.

4.5 Whitefly transmission

Adult insects spread the virus among crops; they are ableto fly long distances, carried by

winds. The rapid spread of the viral disease is caused bythe whitefly high transmission

efficacy. Whiteflies transmit begomoviruses in a persistentcirculative manner. They ingest

TYLCV while feeding on the phloem sap of virus-infectedplants. A single whitefly is able

to acquire TYLCV during a feeding period as short as 15minutes. It is able to infect

a plant during a 15-minute inoculation feeding period. Theefficiency of transmission

increases the longer whitefly feed on plants. Afterwhitefly acquires TYLCV, it takes up

to 24 hours before the insect can transmit the virus (Cohenand Harpaz, 1964). During

this latent period, the virus translocates through thedigestive tract, crosses into the

haemolymph and into the salivary glands where it istransmitted together with the saliva

during feeding. Females are better transmitters than males,although, once acquired,

both genders are able to transmit TYLCV for the rest oftheir lives (Czosnek et al., 2002).

The relationships between begomoviruses and whiteflies arecomplex. TYLCV and some

related viruses present several features of insectpathogens: they affect longevity and

fertility (Rubinstein and Czosnek, 1997), and activate theexpression of genes related to

insect immune response (Luan et al., 2011). TYLCV mayreplicate in its whitefly vector

under stress conditions (Pakkianathan et al., 2015). Arecent report claimed that TYLCV can

be transmitted through seeds (Kil et al., 2016).

4.6 TYLCV management

TYLCV management is usually attempted by controllingwhitefly populations with frequent

insecticide sprays, accompanied by the rapid emergence ofresistance to most insecticides

(Horowitz et al., 2005). Integrated pest management (IPM)methods include preventing

seedling from infestation by whiteflies by using 50-meshnets, ensuring that earlier crops

(such as cotton or pepper) are not planted nearby tomatofields resulting in mass migration

of insects during harvest, and controlling weeds in andaround crops and greenhouse areas.

UV-absorbing plastic covers are also used to reduce insectpopulation in greenhouses and

tunnels (Antignus et al., 2001). Several parasitic waspssuch as Eretmocerus hayati and

Encarsia formosa are whitefly natural enemies and may bevaluable management tools in

IPM programmes (Naranjo, 2001).

The use of virus-resistant varieties is presently the bestalternative to protect crops,

although they do not help control whiteflies and arethemselves sources of virus. Breeding

tomatoes resistant to TYLCV started in the mid-1970s. Itinvolved introgression of

resistance traits found in accessions of several wildtomato species (e.g. Solanum chilense,

S. peruvianum, S. pimpinellifolium and S. habrochaites)into the domesticated tomato

(S. lycopersicum) (Ji et al., 2007). Loci tightly linked toTYLCV resistance, coined Ty-1 to

Ty-6, have been mapped to the tomato chromosomes (Scott etal., 2015). Two Ty-related

genes have been identified, which are involved in TYLCVresistance: Ty-1 encodes an

dRp (Verlaan et al., 2013) and Ty-5 the mrRNA surveillancefactor Pelota (Lapidot et al.,

2015). The mechanism by which these genes provideresistance is not clear. A variety of

transgenic strategies have also been devised, whichinvolves the expression of functional

as well as dysfunctional viral genes (Shepherd et al.,2009). RNA-mediated virus resistance

based on antisense RNA and post-translational genesilencing is efficient, but highly

sequence dependent (Czosnek et al., 2013).

Today, most commercial varieties targeted to TYLCV-infestedregions contain the Ty-1

gene and show good resistance to TYLCV. Pyramiding Ty genesoffers perspectives for

broad-range and durable virus resistance (Vidavsky et al.,2008).

4.7 Other tomato begomoviruses

4.7.1 Tomato leaf curl virus

Tomato leaf curl virus (ToLCV) is the name given to a group

of whitefly-transmitted

geminivirus (family Geminiviridae, genus Begomovirus)causing a destructive disease of

tomato in many regions of India, East Asia and Australia.ToLCV is transmitted by B. tabaci

in a manner similar to the TYLCVs. While ToLCV isolatesfrom Southern India, Australia and

Taiwan have a single genomic component (designated DNA-A),those from Northern India

have two components (DNA-A and DNA-B) (Muniyappa et al.,2000). DNA-A encodes

proteins similar to those of monopartite viruses likeTYLCV. The DNA-B genome encodes

a nuclear shuttle protein while the complementary genomestrand encodes an MP.

Breeding for ToLCV resistance has consisted in using genesproviding resistance to

TYLCV (Ty-1, Ty-3 and Ty-2) and introducing them into localcultivars by classical breeding

(gene pyramiding) (Muniyappa et al., 2002). It isinteresting to note that Ty-2 which provides

resistance to ToLCV in India does not for TYLCV in Israel.Lately, analyses of five generations

progeny of a cross between susceptible and resistantcultivars have shown that genetic

resistance to ToLCV is controlled by a single dominant gene(Yadav et al., 2015).

4.7.2 Tomato mottle virus

A new epidemy affecting tomatoes in 1989 in Florida wascaused by a whitefly-transmitted

virus named Tomato mottle virus (ToMoV). ToMoV, like allthe other begomoviruses, is

transmitted in a circulative persistent manner by B.

tabaci, with similar acquisition, retention

and transmission parameters. In the early 1990s, it greatlyaffected tomato production in

Southeast United States. The epidemic was associated withthe first appearance in Florida

(1988) of the biotype B of B. tabaci (Polston et al., 1993).

TMoV from Florida has been cloned and sequenced (Abouzid etal., 1992). It is a typical

bipartite geminivirus of the New World with a DNA-A of 2601nucleotides (encoding six

genes, similarly to TYLCV) and a DNA-B component of 2541nucleotides (encoding two

genes, similarly to ToLCV).

4.7.3 Other tomato begomoviruses with minor economicimportance

Tomato golden mosaic geminivirus (TGMV) is a typicalbipartite begomovirus (Hamilton

et al., 1981). Very similar to TGMV, Tomato yellow mosaicvirus has been reported

from Venezuela, Costa Rica, Africa and Asia. Symptomsconsist of stunting with severe

deformation of young leaves and shoots, accompanied by abright yellow mosaic on leaves.

Chino del tomate virus (CdTV) Since the 1970s, CdTV hasbeen causing a leaf curl

disease of tomatoes in Sinaloa and Tamaulipas states inMexico (Brown et al., 2000).

Tomato leaf crumple virus (TLCrV) TLCrV is a new virus fromtomato in the Sinaloa state

of Mexico (Paplomatas et al., 1994).

Tomato necrotic dwarf virus (ToNDV) ToNDV is a poorlycharacterized whitefly

transmitted virus from California (United States) (Larsenet al., 1984).

5 Transmission of RNA viruses by whiteflies

5.1 Tomato infectious chlorosis virus and Tomato chlorosisvirus

The Crinivirus spp. (genus Crinivirus, familyClosteroviridae) represent a group of viruses

that emerged over the past few decades in association withthe worldwide emergence of

Figure 5 Co-infection of tomato plant with Tomato yellowleaf curl virus (top left) and Tomato infectious

chlorosis virus (top right); Tomato infectious chlorosisvirus in the left row in a greenhouse (bottom left)

(photographs: A. Koren).

the whiteflies B. tabaci B biotype and T. vaporariorum(Wisler et al., 1998; Tzanetakis et al.,

2013;). Crinivirus spp. were reported to infect field andgreenhouse tomato crops in the

Caribbean islands, Taiwan and in countries around theMediterranean basin. Criniviruses

have a bipartite ssRNA genome with the two segmentsseparately encapsidated, and are

transmitted by several species of Bemisia and Trialeurodeswhiteflies in a semi-persistent

manner (Wintermantel 2004).

Two Crinivirus spp. emerged as a problem in tomatoproduction, Tomato infectious

chlorosis virus (TICV) and Tomato chlorosis virus (ToCV).TICV was first identified in field

grown tomato crops in 1993 in California (Duffus et al.,1996). TICV is efficiently transmitted

by whiteflies.

A Crinivirus sp. that was distinct from TICV in terms ofRNA sequence, vector specificity,

and host range was isolated and named ToCV (Wisler et al.,1998b). TICV is transmitted

solely by the greenhouse whitefly T. vaporariorum, whereasToCV is transmitted by

a number of whitefly species which include the greenhousewhitefly; the banded wing

whitefly (T. abutilonea); and the B. tabaci biotypes A, Band Q (Navas-Castillo 2000).

The B biotype has been shown to be the most efficientvector for ToCV transmission

(Wintermantel and Wisler, 2006).

Both TICV and ToCV induce practically indistinguishableyellowing disease in tomato,

which includes interveinal yellowing and thickening ofmature leaves, while the new

growth at the plant apex appears normal. Disease symptomsusually appear 3–4 weeks

following inoculation (Fig. 5). Fruit of infected plantsare smaller and decreased in number,

the ripening process is impeded, all of which results inyield and economical losses. Both

viruses are phloem limited and infected plants carry lowviral titers, which complicates

accurate diagnostics. Tests have been devised todiscriminate between TICV and ToCV

(Papayiannis et al., 2011).

5.2 Pepino mosaic virus

Pepino mosaic virus (PepMV) (genus Potexvirus, familyFlexiviridae), was initially

isolated from pepino (Solanum muricatum) in 1974 in Peru(Jones et al., 1980), and first

reported in tomato in 2000 (van der Vlugt, 2000). Itquickly became a major disease

of greenhouse-grown tomato worldwide. PepMV can be spreadby B. tabaci and T.

vaporariorum (Noël et al., 2013); however, most of thedamage is caused by mechanical

transmission.

PepMV has flexuous rod-shaped particles of about 580 nm inlength, which encapsidate

a (+)ssRNA genome of about 6.4 kb (Verhoeven et al., 2003).The PepMV genome encodes

five proteins: an RdRp involved in virus replication; threeproteins involved in cell-to-cell

movement coded by overlapping genes organized into a triplegene block (proteins

TGBp1, TGBp2 and TGBp3); and the coat protein (CP).

PeMV causes a wide variety of symptoms on tomato fruit(especially marbling) and

leaves (distorted upright). European and US strains shareonly 80% nucleotide sequence

identity; some strains are recombinants (Pagán et al.,2006; Hanssen et al., 2008). PepMV

is transmitted mechanically from plant to plant at highrates. It is also transmitted through

the seed, contributing to its long-distance spread(Córdoba-Sellés et al., 2007). The ability

of bumble bees (Bombus impatiens), used for pollination, toacquire and transmit PepMV

was experimentally demonstrated in greenhouse-growntomatoes. The virus was detected

in leaf, fruit and flower samples of formerly healthyplants. In commercial greenhouses

where PepMV was present, almost all plants and bumble beeswere PepMV positive

(Shipp et al., 2008). No defined mechanisms of virustransmission were described other

than distribution of infected pollen.

At present, there are no efficient PeMV-resistant tomatocultivars. A limited number

of accessions of wild tomato species S. chilense, S.peruvianum and S. pseudocapsicum

exhibit good levels of resistance to PeMV (Soler-Aleixandreet al., 2007); however, it seems

that tapping these sources to introgress resistance incultivated tomato lines is a difficult

task. Cross-protection with mild PeMV strains, whethernatural or engineered, offers

some relief (Chewachong et al., 2015). It is commonpractice in the greenhouse in the

Netherlands and Belgium to inoculate seedlings with mildstrains of PeMV to cross-protect

crops against the virulent PeMV strains.

5.3 Tomato torrado virus and tomato marchitez virus

In 2001, burn-like necrotic spots were observed on tomatoleaves in Southern Spain

(Verbeek et al., 2007). The syndrome was locally referredto as ‘torrado’ (roasted) disease.

The virus also caused necrotic streaks on stems and fruits.The disease agent was named

Tomato torrado virus (ToTV). ToTV was found in Spain,Canary Islands, Panama, Poland,

Hungary and Australia, indicating that this virus migratedrapidly over large distances

(Pospieszny et al., 2007). ToRV was isolated from theinfected plant. It consists of isometric

particles with a diameter of approximately 28 nm. The viralgenome is split between

two (+)ssRNA molecules of 7221 (RNA1) and 4898 nucleotides(RNA2). The viral capsid

contains three coat proteins of 35, 26 and 24 kDa,respectively (Verbeek et al., 2007).

In 2003, a disease similar to ToTV, causing leaf, stem, andfruit necrosis was observed in

tomato crops in Mexico, and named locally as ‘marchitez’(wilted) disease. It was coined

Tomato marchitez virus (ToMarV) (Verbeek et al., 2008).Morphology, number and size of coat

proteins, and number of genomic RNAs are similar to thoseof ToTV (Verbeek et al., 2008).

Nucleotide sequence analyses revealed that ToMarV isrelated to but distinct from ToTV. The

name Torradovirus was proposed for the new genus thatincludes ToTV and ToMarV (van der

Vlugt et al., 2015). In contrast to ToTV, ToMarV wasreported so far only in Mexico.

Whiteflies are the semi-persistent vector of ToTV andToMarV. ToMarV is efficiently

vectored by the greenhouse whitefly T. vaporiarium (Verbeeket al., 2014). T. vaporariorum

could transmit ToMarV efficiently to a new host for atleast 8 hours after becoming

infected. The whitefly B. tabaci was shown to efficientlytransmit ToTV to tomato and to

other Solanaceous crops, including potato, eggplant, pepperand tobacco, and weed

hosts (Amari et al., 2008).

6 Viruses spread by leafhoppers

6.1 Beet curly top virus

Although tomato is not a preferred host of Beet curly topvirus (BCTV), the virus started to

be detected in the mid-1960s (Bennett, 1971). However, inthe past two decades, climate

warming and dry weather led to a great increase of thenumber of leafhopper vectors.

Polymerase chain reaction (PCR) with general andspecies-specific primers was used to

establish that BCTV comprises two predominant speciesassociated with tomato curly

top disease: Beet mild curly top virus and, to a lesserextent, Beet severe curly top virus

(BSCTV) (Chen et al., 2010).

BCTV is a geminivirus with a single genomic component(monopartite). It is a member

of the genus Curtovirus (Stenger, 1994). The only knownvector of BCTV is the beet

leafhopper (Circulifer tenellus) (Cicadellidae), which isnative to the Western United States.

Both the virus and its vector have very wide host ranges(Guzmán et al., 1996).

Leafhoppers lay eggs that hatch to several immature instarsbefore becoming adults.

Some of them overwinter as eggs, some as adults, and someas immatures. They all feed

by sucking sap from the plant host phloem. Their feedingbehaviour is similar to that of

aphids. The mouthparts, surrounded by the salivary sheath,reach the phloem of host

plants and feed on the sap. C. tenellus acquires andtransmits BCTV to tomato during a

brief feeding period on the phloem (Stafford and Walker,

2009). Once the virus is ingested,

it moves from the digestive tract to the salivary glands.Infected leafhoppers are able to

transmit the virus for the rest of their lifetime, thuslong distance spread is common. BCTV

does not replicate within the leafhopper, does not causeobvious damage to the vector

and is not transovarially transmitted to offspring(Hogenhout et al., 2008).

Plants begin to show symptoms about 7–14 days after theyare first infected by

a leafhopper. Severity of the disease depends on the age ofthe plant at the time of

infection. Infected seedlings often die before settingflowers. Plants infected after the

seedling stage survive, but are yellow and stunted. Leavesof infested plants are dwarfed,

crinkled, rolled inward and cupped upward. Veins on theunderside of leaves usually have

a purple discolouration, phloem tissues become necrotic.Yields are reduced and fruits

ripen prematurely. Efforts to breed tomato-resistant BCTVhave been largely unsuccessful.

However, some tomato varieties may be resistant byrepelling the virus vector (Thomas and

Martin, 1971). Spraying tomatoes with insecticides does notcontrol the disease because

leafhoppers migrate from distant places and do notreproduce or remain in tomato fields.

7 Genetics tools to control viral infestation of tomatoes

7.1 Control of infestation

A wide range of measures are taken to avoid infection earlyafter planting, when plants

are the most susceptible. It is advised to select growingareas distant from crops known to

be breeding grounds of virus vectors and are harvestedbefore tomato (e.g. cotton, bell

pepper) to avoid the sudden invasion of swarms ofviruliferous insects. Before planting,

precautions include removal of weeds and of tomato plantsgrown the previous season,

reparation of greenhouse/nethouse to minimize insectinvasion, and use of virus-free

seedlings. During the early periods of growth, it iscrucial to monitor insect populations

using traps and to look for suspect symptoms.

Inoculation of tomato plants by insect vectors takes only afew minutes. Once a plant is

inoculated, infection cannot be stopped. Although thedamage to crops can be minimized

by using virus-resistant crops, the virus is still able toreplicate and spread in the plant,

sometimes with a lesser efficacy, and can be transmitted byvectors to other plants,

whether susceptible or resistant. Early eradication ofinfected plants may avoid virus

spread to other plants. Therefore, it is crucial to rapidlydetect and identify both virus and

vector. In the following paragraphs, we will discuss thecutting-edge methods of diagnosis

of tomato viruses and of breeding using molecular tools,whether classical or by means of

genetic engineering.

7.2 Current and prospective diagnosis methods

7.2.1 Classical tools

Tomatoes are prone to infection by many viruses thatpresent similar symptoms and

patterns of disease development. Hence preciseidentification is an arduous task.

Moreover, because tomato viruses replicate and spreadrather fast, there is only a narrow

window from the time plants are inoculated until theybecome a virus source for vectors,

during which viruses need to be identified and the plantseradicated. Hence the virus

must be identification in the shortest time possible. Thetraditional detection methods

rely either on the immune properties of viral proteins,usually the coat protein, or the

sequence of the virus genome(s), whether RNA or DNA. Thefirst group includes enzyme

linked immunosorbent assay (ELISA) and immunofluorescence(IF). The second group

includes PCR and fluorescence in situ hybridization (FISH).These methods may take

several days to yield an answer and are geared towards thedetection of expected viruses.

Other technologies have been applied to the early detectionof plant pathogens such as

flow cytometry, thermography, fluorescence andhyperspectral imaging, and biosensors

including microarrays (reviewed by Fang and Ramasamy, 2015).

7.2.3 Biosensors and microarrays

The advent of biosensors has brought in new and promisingapproaches for the detection

of animal and plant pathogens. However, much research anddevelopment is still needed

before biosensors become routine tools. In these devices,microscopic poles are attached

to antibodies, nucleic acids or enzymes that trap pathogenproteins or nucleic acids,

detected by a sensor based on electrical, chemical,electrochemical, optical, magnetic

or vibrational signals. For example, gold nanorods linkedto antibodies have been used

to detect two orchid viruses within 10 minutes, Cymbidiummosaic virus (CymMV) and

Odontoglossum ringspot virus with limits of detection of 3orders of magnitude higher than

that provided by ELISA (Lin et al., 2014). In anotherinteresting development, antibodies

against PVY, CMV and Tobacco rattle virus (TRV) wereelectro-inserted into the membrane

of Vero cells (derived from African green monkey kidneyepithelial cells); the attachment of

PVY, CMV or TRV particles to the homologous antibodiescaused a virus-specific change

of the cell membrane electric potential (Perdikaris et al.,2011). This system was able to

process 96 samples within 70 min.

Different microarray platforms have been developed whereprobes complementary

to various virus sequences are attached to a solid support,whether a membrane or

a microscope glass slide. The probes may be cDNAs orsynthetic oligonucleotides

spotted on, or synthesized in the first place onto, thearray surface. Thousands of probes

representing a large panoply of viruses suspected to bepresent in the scrutinized samples

can be arrayed onto a single microscope glass slide. Themicroarray can then be exposed

to fluorescently labelled DNA or cDNA from the sample to betested, and finally scanned

using a microarray scanner. Hence, in a single assay, themicroarray is able to reveal

within three days if any one of the many virusesrepresented on the array is present in

the sample.

Microarrays have been applied to the detection of plantviruses from the early 2000s

(Lee et al., 2003; Hadidi et al., 2004). They were shown tobe able to detect several virus

species (with less than 80% sequence identity) infecting asingle crop (e.g. Potato viruses

Y, X, A and S), as well as virus variants with greater than90% sequence identity (Boonham

et al., 2003). A 40-mer oligonucleotide DNA microarrayaimed at the diagnostic of tomato

viruses was implemented (Tiberini et al., 2010). The arraycontained about 300 probes

for the potential simultaneous detection of ten majortomato viruses and their strains:

CMV and its satellite RNA, TILC, ToCV, TSWV, PepMV, TMV andToMV. The tomato virus

microarray may be expanded to include more oligonucleotideprobes for the discovery of

additional emerging tomato viruses and strains. It has thepotential to be used in disease

management and certification programmes.

7.2.4 Next-generation sequencing and metagenomics

Plant virology has reached new heights with the applicationof mass sequencing (or next-

generation sequencing, NGS) to the field of virus diagnosisand discovery (Barba et al.,

2014). The sequence-based diagnosis relies on the naturalmechanism by which plants

supress virus infection (whether RNA or DNA) by a mechanismcoined ‘RNA silencing’ or

‘RNAi’ (Voinnet, 2005). Upon infection, the silencingmachinery recognizes and specifically

destroys single- and double stranded RNA moleculeshomologous to the invader,

using virus-specific 21–24 nucleotide-long interfering RNAs(siRNA) as a guide (recently

reviewed by Zhang et al., 2015). NGS of siRNAs can providethousands to millions of

sequences from which virus genome fragments can beassembled, identifying not only

the virus (including previously unknown viruses) but alsoits titer. NGS has been used

to identify several known and previously unknown viruses ininfected tomatoes, even at

concentrations undetectable by other methods: TSW (Mitteret al., 2013), TYLCCNV (Yang

et al., 2011), PepMV (Li et al., 2012), ToMoV (Li et al.,2013), TSWV (2011) and Tomato

necrotic stunt virus (Li et al., 2012).

Metagenomics, the sequencing and analysis of the genomesfrom organisms sampled

from the environment, was lately added to the tool box ofplant virologists (Adams et al.,

2009; Roossinck, 2012). The viruses found with this methodinclude (1) virus species or

isolates already known to infect the scrutinized plants;(2) known virus species or isolates

that have not been found previously in the surveyed plants;and (3) completely novel

viruses, unrelated to known viruses (Stobbe and Roossinck,2014). Since the majority

of known plant viruses are exclusively vector-transmitted,examination of insect vectors

collected from various geographical regions presents aunique avenue for exploring the

diversity and movement of plant viruses (Ng et al., 2011).Such a survey of tomato viruses

was recently performed using whiteflies collected fromtomato cultures in Guatemala,

Israel, Puerto Rico, Spain, and the United States (Rosarioet al., 2015). It revealed the

presence of known as well as exotic and novel begomoviruses.

7.3 Molecular-assisted breeding and genes for virusresistance

The cultivated tomato is susceptible to many abiotic (heat,drought, salt) and biotic (viruses,

fungi, bacteria) stresses. Most of the alleles conferringvarious resistances have been

lost during selection for yield, shape and colour, becausethey are linked to undesirable

horticultural traits (Bai and Lindhout, 2007). Breeding forresistance to tomato viruses

consisted in identifying resistant traits from wild tomatospecies such as S. pimpinellifolium,

S. peruvianum, S. chilense, S. habrochaites and S.cheesmaniae, and introgressing them

into the domesticated tomato S. lycopersicum by crossingand selection. As a result, the

resistant lines and cultivars contain fragments ofchromosomes from wild tomato genitor(s)

that bear the resistance gene(s) on the chromosomalbackground of domesticated tomato.

Molecular geneticists are able to distinguish the DNA fromthe wild tomato(es) from the

DNA of the cultivated tomato by their sequence polymorphism(Hanson et al., 2000).

Breeders can combine (pyramiding) different sources andtypes of resistance in a single

genotype. Today, most elite commercial cultivars possess alarge array of resistances to

viruses, fungi and bacteria.

With the advent of genetic analyses backed up by masssequencing of tomato genomes,

molecular markers that provide saturated genetic maps ableto tag resistances have been

developed (Ganal, 2013; Lee et al., 2015).Single-nucleotide polymorphisms (SNPs) are

among the most common types of genetic variation widelyused in tagging genes of

interest. SNPs can be utilized to develop rapid tests basedon a combination of PCR and

restriction enzyme analyses (such as RFLP-PCR, AFLP, CAPS).Expressed genes (expressed

sequence tags, ESTs) can serve as markers for genelocalization. Markers derived from

microsatellites or simple sequence repeat (SSR), based onshort tandem repeats, are able

to detect a high level of polymorphism even in closelyrelated genotypes such as the

cultivated tomato (Shirasawa et al., 2010; Ganal, 2013).Molecular markers have been

instrumental in identifying genes conferring resistance totwo major insect-transmitted

tomato viruses: TYLCV and TSW.

Several accessions of wild tomato species have beenidentified as bearing TYLCV

resistances: S. chilense (Zamir et al., 1994; Agrama andScott, 2006), S. habrochaites

(Hanson et al., 2000; Vidavsky and Czosnek, 1998) and S.peruvianum (Friedmann et al.,

1998). The known loci associated with TYLCV resistance havebeen coined Ty1 to Ty6. A

list of DNA markers for tagging the Ty1-6 loci have beencompiled (Lee et al., 2015). Two

allelic loci from S. chilense accessions LA1932 and LA2779,named Ty1 and Ty3, were

located on chromosome 6. Using susceptible (cv Moneymaker)and resistance lines and

segregating populations, molecular markers helped tofine-map, clone and sequence the

gene conferring the Ty1/3 resistance; it encodes aDFDGD-class RdRp (Verlaan et al.,

2013). Another TYLCV recessive resistance gene derived fromS. peruvianum was located

on chromosome 4, termed Ty5. It was identified ashomologous to the messenger RNA

surveillance factor Pelota implicated in the ribosomerecycling phase of protein synthesis

(Lapidot et al., 2015). The identity and function of theresistance genes have been

confirmed using populations segregating for resistance,gene silencing to convert resistant

to susceptible plants, and overexpression in transgenictomatoes to convert susceptible to

resistant plants. The other Ty loci have not yet yieldedthe resistance gene(s). Ty2 resistance

originated from S. habrochaites B6013 was recentlyfine-mapped on chromosome 11

(Yang et al., 2014). Ty4 was identified on chromosome 3from S. chilense LA1932 and

LA2779 (Ji et al., 2009) and Ty6 was localized onchromosome 10 from S. chilense LA2779

(Scott et al., 2015).

Diverse tomato cultivars show resistance to Tospoviruses(Saidi and Warade, 2008).

TSWV resistance traits have also been identified in S.habrochaites accessions PI127826

and LA1353 and in S. habrochaites var. glabratum PI134417and LA1223. To date,

eight TSWV resistance genes (Sw1a, Sw1b, sw2, sw3, sw4,Sw-5, Sw-6 and Sw-7) have

been reported (Price et al., 2007; Saidi and Warade, 2008).Among these, Sw-5 is the

most studied and utilized for developing TSWV-resistanttomato varieties. Sw-5 was

characterized in S. peruvianum on chromosome 9 andintrogressed in the cultivated

tomato (Stevens et al., 1991); it confers a broadresistance against Tospoviruses, including

TSWV, TCSV and GRSV (Boiteux and Giordano, 1993). Thedominant resistance locus Sw5

contains two highly homologous (95%) resistance genes namedSw5-a and Sw5-b, which

encode proteins of 1245 and 1246 amino acids, respectively.The two proteins possess

a coiled-coil domain, a nucleotide-binding adapter, and aleucine-rich repeat domain;

promoter and terminator regions of the genes are alsohighly homologous (Spassova

et al., 2001). Both genes resemble the tomato nematode andaphid resistance gene Mi

and, to a lesser extent, the Pseudomonas syringaeresistance gene Prf. Transformation of

Nicotiana tabacum cv. SR1 plants revealed that the Sw5-bgene, but not the Sw5-a gene,

is necessary and sufficient for conferring resistance toTSWV. Gene-based markers for Sw-5

used in breeding programmes are listed in Lee et al. (2015).

The whole-genome sequencing of many tomato cultivars andwild species (Aflitos et al.,

2014) offers inexhaustible sources of DNA variations thatcould be used for gene tagging

and function discovery (Salgotra et al., 2014). Comparingthe sequences of susceptible

and resistant tomato lines and the wild tomato speciesproviding the resistant traits may

help increase the panoply of resistance genes available tobreeders (Aflitos et al., 2014;

Bolger et al., 2014; Strickler et al., 2015).

7.4 Genetic engineering for virus resistance

Transgenic strategies have been implemented to developtomato lines resistant to insect

transmitted viruses (Shepherd et al., 2009). As for today,there is no genetically engineered

virus-resistant (or other) tomato commercially available tobe used in the field or in the

greenhouse (http://time.com/3840073/gmo-food-charts/).

7.4.1 Pathogen-derived virus resistance

This type of engineered resistance was adapted from thepathogen-derived resistance

(PDR) concept, which is based on the assumption that aplant may be protected from

a pathogen by expressing genes (wild, mutated or truncated)from this very pathogen

(Sanford and Johnston, 1985). Depending on the constructsand of the genes, the

mechanism of resistance may be very different.

Truncated Rep gene (encoded by the C1 gene) of TYLCV wasexpressed in inbred tomato

lines and challenged in the field with viruliferouswhiteflies. A truncated Rep version was

also introduced in transgenic tomato in the antisenseorientation. Whether Rep sequences

were introduced in the sense or antisense orientations, nosymptoms were observed and

no TYLCV genomic DNA was detected in the transformed plants(Yang et al., 2004). In

a similar study involving the TYLCV close relative TYLCSV,the Rep N-terminal 130 aa

were sufficient to inhibit C1 transcription and virusreplication, and to confer resistance in

transgenic plants (Sardo et al., 2011). Antisense RNAtargeted to the TYLCV Rep mRNA

was expressed in N. benthamiana. The replication of TYLCVin the transgenic plants was

almost completely inhibited and resistance was effectiveduring at least two generations

of progeny (Bendahmane and Gronenborn, 1997).

Transgenic tomato lines immune to TSWV were obtained byintroducing the

nucleocapsid (N) gene of TSWV into the plant genome (Nervoet al., 2003). Despite

the presence of a high amount of transgenic transcripts,

transgenic proteins have not

been detected, suggesting a mechanism of resistancemediated by RNA, such as PTGS.

Indeed, the resistant plants produced 24 and 21–22 ntN-gene-specific siRNA classes.

Interestingly, starting at the fifth transgenic generation,some individual plants showed

a TSWV-susceptible phenotype associated with thedisappearance of siRNAs and with

hyper-methylation of the transgene (Catoni et al., 2013).

Partial resistance to CMV was achieved by expressing adefective viral replicase gene

in transgenic tomato (Gal-On et al., 1998). Resistance wasalso achieved by expressing an

RNAi construct containing an 1138 bp inverted repeatdirected against a CMV-O replicase

gene in transgenic tomato plants (Ntui et al., 2014).Transgenic plants inoculated with

CMV strains O and Y showed good levels of resistance(symptomless or ameliorated

symptoms). The resistance was correlated with PTGS.

7.4.2 Expression of antibodies, nucleases and chaperonines

Other transgenic strategies include the expression ofrecombinant antibodies in plant cells

Safarnejad et al., 2011). Antibodies can be directedagainst the coat protein or against

non-structural proteins. This was achieved with TSWV andTYLCV.

Transgenic N. benthamiana plants expressing high levels ofa cytosolic single-chain

variable fragment (scFv) recognizing the TSWV N proteinwere resistant to the virus, but

the accumulation of G protein-specific scFvs in theendoplasmic reticulum (ER), where the

virus accumulates prior to acquisition by an insect vector,did not inhibit virus transmission

(Prins et al., 2005). In another study, nine scFvsrecognizing conserved domains in TSWV

MP (NSM) were expressed in the cytosol of transgenictobacco plants. Two of the scFvs

expressed at high levels achieved a significant delay inthe onset of disease symptoms

(Zhang et al. 2008).

Two scFvs (ScRep1 and ScRep2) recognizing differentepitopes of the TYLCV Rep were

generated using phage display libraries. Both ScRep1 andScRep2 accumulated to high

levels in the cytosol of infiltrated tobacco plants, andthe antibodies were able to bind

their target antigen with high affinity (Safarnejad et al.,2008). A ScRep1 fusion with green

fluorescent protein reduced the accumulation of virus DNAin transgenic N. benthamiana,

the first demonstration of antibody-mediated resistanceinvolving a DNA virus (Safarnejad

et al., 2009). In another study, a scFv that recognizes thecoat protein of Tomato leaf curl

New Delhi virus in vitro can also bind to a recombinantcoat protein in vivo. By adding

a nuclear localization signal into the scFv constructresulted in the nuclear import of the

antibody–antigen complex, indicating that recombinantantibodies can be targeted to the

nucleus and will bind to geminivirus coat proteins,interrupting the virus replication (Zakri

et al., 2012).

Zinc-finger nucleases have been used to cleave begomoviralgenes. The expression

in Arabidopsis of an artificial zinc-finger proteins(six-mer) with a high affinity for the Rep

protein of TGMV and BCTV produced transgenic plants withreduced or no replication of

BCTV (Sera, 2005).

The mode of interaction of begomoviruses and their whiteflyvector was exploited

to produce virus-resistant plants. Plant viruses (perhapsall) transmitted in a circulative

manner by their insect vectors avoid destruction in thehaemolymph by interacting with

an endosymbiotic GroEL homologue. First shown for the M.persicae-transmitted PLRV,

a GroEL homologue produced by the Buchnera endosymbioticbacteria exhibited affinity

for the virus (Van der Heuvel et al., 1994). Similarly, theTYLCV CP interacted in vivo and in

vitro with the B. tabaci GroEL; disturbing this interactioninhibited virus transmission. This

phenomenon was exploited to generate transgenic tomatoplants, expressing the whitefly

GroEL in their phloem. It was thought that followinginoculation, TYLCV particles will be

trapped by GroEL in the plant phloem, thereby inhibitingvirus replication and movement,

rendering the plants resistant. Indeed, GroEL-expressingtomatoes were resistant to

TYLCV; in vitro assays indicated that the sap of resistantplants contained GroEL-TYLCV

complexes (Akad et al., 2007).

7.4.3 Inducing resistance by post-transcriptional genesilencing and RNAi

Most examples of PDR for plant viruses occur through PTGS(Waterhouse et al., 2001). The

plants transformed with viral nucleic acids (entire ortruncated genes as well as non-coding

regions) mobilize the antiviral response centred onRNA-based silencing machinery, which

ultimately leads to the specific degradation of the genomeof the invading related virus,

resulting in resistance (Baulcombe, 1996, 2004). Intransgenic plants, small interfering RNA

(siRNA) molecules of 21–25 nt, derived from the transgene,mediate the sequence-specific

binding that directs the silencing machinery to targetRNAs. siRNA accumulation in tomato

plants infected with TYLCV (Lucioli et al., 2003) reflectsthe role of the RNAi pathway as

a natural defence, also against DNA viruses such asgeminiviruses. On the other hand,

certain viral genes can suppress RNA silencing, and thuslessen the effectiveness of

transgenic resistance (Qu and Morris, 2005; Burgyán andHavelda, 2011).

The RNAi mechanism has been applied for engineering virusresistance (Tenllado et al.,

2004). RNAi is triggered by the expression dsRNAshomologous to viral sequences obtained

by designing hairpin-like constructs containing the senseand antisense orientation of the

target viral sequence separated by an unrelated sequence(sometimes and intron) (Wesley

et al., 2003). The dsRNA region is processed into small

interfering RNAs (siRNAs), which

guide silencing complexes to target regions on RNA or DNA.In plants, the predominant

action of silencing complexes on RNA seems to be cleavage,leading to PTGS, whereas

targeted DNA regions often become methylated andtranscriptionally silenced (TGS)

(Vanderschuren et al., 2007). RNA viruses can only beaffected by PTGS, whereas, for

geminiviruses, both silencing mechanisms may be applicable(Vanitharani et al., 2005). The

efficiency of PTGS was confirmed for TYLCV and relativeviruses. Non-coding conserved

regions from the genome of TYLCV, TYLCV-mild, TYLCSV,TYLCMalV and TYLCSV-Spain

were used to design a hairpin construct that can triggerbroad resistance against these

different viruses. The silencing construct was cloned intoan Agrobacterium-binary vector

and used to infiltrate tomato and N. benthamiana plants. Ahigh level of resistance to

all three viruses was obtained when plants were inoculatedwith TYLCV, TYLCV-Mld

and TYLCSV-Spain using whiteflies. TYLCV-specific siRNAsaccumulated in the silenced

plants (Abhary et al., 2006). A similar approach was taken,although the coding region

of the ToLCV C4 gene was targeted. Double-strand(ds)RNA-producing constructs were

generated using up to 200 bp of C4 in the sense andantisense orientations separated by

different introns behind the CaMV 35S promoter. Theconstructs were used to transform

tomato plants. These plants showed a reduction of up to 65%in the expression level of the

C4 gene. Resistance to ToLCV was not probed (Praveen etal., 2010).

Transient expression of siRNA can be achieved using plantviruses as vector. TRV is

one of the common viral vectors used for virus-induced genesilencing (VIGS). VIGS is

based on a RNA-mediated defence mechanism against virusinfection that is related to

PTGS. VIGS vectors have also been developed with thegeminiviruses TGMV, CaLCuV

and ACMV (Kjemtrup et al., 1998; Turnage et al., 2002;Fofana et al., 2004), indicating

that silencing is also triggered by DNA viruses. Expressionof exogenous dsRNAs that

interferes with the viral counteraction should constitute apromising approach to increase

plant resistance. TRV-based gene silencing has been themethod of choice to verify the

identity and the potency of resistance genes identified bymolecular-assisted breeding

and map cloning (e.g. Verlaan et al., 2013). This methodhas also allowed to identify

genes involved in resistance to TYLCV in virus-resistanttomato plants and to identify

their hierarchy in the resistance network (Eybishtz et al.,2009; Czosnek et al., 2013; Sade

et al., 2014).

7.4.4 Targeting insect genes involved in virus acquisitionand transmission

In the future, it might be possible to use interfering RNAto inhibit the function of genes

involved in virus transmission by insect vectors.RNAi-based silencing has already been

used to deplete the expression of genes in the TYLCV vectorB. tabaci, and lately in the

TSW vector F. occidentalis.

Long dsRNA targeting genes specifically expressed in themidgut and salivary glands

were injected into the whitefly body cavity, leading todepletion of gene expression by up

to 70%. Injecting dsRNA targeting the whitefly Drosophilachickadee homologue disrupted

the actin network in the whitefly developing eggs, causingconspicuous malformations

(Ghanim et al., 2007). Recently, it was shown that feedingwhiteflies on a tomato leaflet

soaking in a solution of dsRNA targeting the knottin-1 geneof B. tabaci (but not knottin-3)

not only reduced the expression of the gene, but alsoincreased by several orders of

magnitude the amount of TYLCV acquired by these insectsfrom infected tomato plants,

indicating that this gene is involved in regulating theamount of virus in the insect (Hariton

Shalev et al., 2016).

Using a microinjection system, dsRNA targeting the vacuolarATP synthase subunit B

(V-ATPase-B) gene was injected into the haemocoel of femalethrips. Gene expression

analysis revealed significant reductions of V-ATPase-Btranscripts and protein, associated

with increased mortality and reduced fertility(Badillo-Vargas et al., 2015).

7.4.5 Engineering virus-resistance by genome editing

The genome editing method, known as clustered regularlyinterspaced short palindromic

repeats, and their associated Cas9 proteins (CRISPR/Cas9)are revolutionizing the fields of

genetics and genomics. The CRISPR/Cas9 system is part of aprokaryote immune system

against invading foreign DNAs (Sorek et al., 2013). TheCas9 protein is a RNA-directed

endonuclease able to recognize and cleave nucleic acids onthe basis of sequence

complementarities and to modify the targeted sequences (Hsuet al., 2014). Cas9 can

be targeted to specific DNA genomic sequences byengineering separately an encoded

small guide RNA (sgRNA) with which it forms a complex(Doudna and Charpentier, 2014).

Thus, only a short RNA sequence must be synthesized toconfer recognition of a new

target. RNA-guided cleavage paired with donor-guided repairallows easy introduction of

any desired modification in a living cell.

During the last few years, the CRISPR/Cas9-based systemshave become the method

of choice for genome editing by introducing or correctinggenetic mutations in a wide

variety of biological contexts: cell lines, animals(including humans) and plants (Belhaj

et al., 2015), as well as human RNA and DNA viruses (Priceet al., 2015). It is versatile as it

can be used to introduce or delete a number of differentgenes at a time.

Very recently, the CRISPR/Cas9 system was applied to induceresistance to TYLCV

in N. benthamiana. sgRNAs targeted against TYLCV CP, Repand the intergenic region

that contains the virus origin of replication weredelivered using a TRV vector into N.

benthamiana overexpressing the Cas9 endonuclease (Cas9OEplants) (Ali et al., 2015).

Significant reduction or attenuation of disease symptomswas observed. A similar study was

conducted with the tomato leafhopper-transmittedgeminivirus BSCTV in N. benthamiana

and in Arabidopsis (Ji et al., 2015). Overexpression ofsgRNA-Cas9 specifically targeting

the viral DNA genome sequences resulted in virus-resistantplants. This strategy is

working with other begomoviruses such as Bean yellow dwarfvirus (BeYDV)-infecting N.

benthamiana (Baltes et al., 2015). NGS analysis of indelswithin the viral genome suggested

that Cas9 introduces the dsDNA breaks at the targeted sitesand that most mutations were

1–2 bp indels.

The CRISPR/Cas9 system targets any viral sequence andinterferes with geminivirus

replication and systemic movement. The small size of theguide components enables

the stacking of several sgRNA in a single plant, therebydirecting several nucleases

against a single virus or against multiple viruses in mixedinfections (Baltes et al., 2015).

Engineering-resistant tomato plants have not been reportedyet, although the CRISPR/

Cas9 system works efficiently in tomato (Brooks et al.,2014; Pan et al., 2016). Besides

conferring resistance to TYLCV and BSCTV in model plants,the CRISP/Cas9 systems

remain a potential candidate. A road map for using thistechnology to confer resistance to

TSWV is available but not yet implemented (Martinelli etal., 2014).


Domestication of tomato from the wild and selection forhigh yield and good fruit quality

have resulted in the loss of many of the alleles conferringresistance to biotic and abiotic

stresses. As a result the modern tomato is prone todiseases caused by viruses, bacteria

and fungi, and to stresses induced by heat, salt anddrought (Bai and Linhout, 2007).

Geneticists and breeders have identified genes conferringvarious resistances in wild

tomato species and are working hard to re-introduce thesegenes in the cultivated tomato

(Bauchet and Causse, 2014).

In this chapter we have described the most importantinsect-transmitted viruses (and

some less important) that infect tomato plants. The elitetomato cultivars include genes

for resistance against a maximum number of pathogens (e.g.TSWV, TYLCV, BCTV and

TMV), especially those present in the growing area. Thesegenes are usually tagged with

specific polymorphic DNA markers (Labate et al., 2007;Liedl et al., 2013), and the large

commercial companies run their own diagnosis laboratories.Since not all the cultivated

tomatoes are resistant to most viral diseases, strategieshave been devised to protect

plants from the virus insect vectors by using mulches,natural enemies and mostly by

spraying chemicals. The advent of new technologies such asgene silencing may help

control insect vectors (Huvenne et al., 2010). Thesequencing of the entire genomes of a

large number of tomato varieties, susceptible and resistantto various viral diseases may

increase the pool of resistance genes that will beavailable to breeders. The sequencing of

their insect vector (Leshkowitz et al., 2006; TheInternational Aphid Genomics Consortium,

2010; Myzus persicae database:https://www.aphidbase.com/node_94263/Myzus-DB)

may help better understand plant–insect–virus co-evolution.

Understanding the triangular relationshipvirus–vector–plant may help disturb virus

transmission. Insects play specific roles in thetransmission of viruses. In several cases,

the diseased plant develops symptoms that make them moreattractive to viruliferous

insects (Fang et al., 2013). While in most cases thepathogen does not affect its insect

vector directly, there are several plant viruses thatmultiply in the insect vector as well

as in their plant host, and such vector insects often showreduced reproduction and

shorter lifespan. Most of the insect/pathogen associationsare highly specific and involve

sophisticated molecular mechanisms that regulate theuptake, retention and transmission

of the pathogen by its insect vector.

Modern diagnostic tools are aiming as fast and accurateidentification of viruses, among

a panoply of known and unknown pathogens infected a givencrop. Genetic engineering,

genome editing and metagenomics offer methods to induceresistance in tomato and to

downplay the potency of insects to vector viruses.


Several websites provide information on the epidemiology,disease management and

resistance of tomato virus diseases, some includephotographs of symptoms:

https://en.wikipedia.org/wiki/List_of_tomato_diseases

http://vegetablemdonline.ppath.cornell.edu/factsheets/Viruses_Tomato.htm

https://www.rhs.org.uk/advice/profile?PID=250

http://www.aces.edu/pubs/docs/A/ANR-0836/ANR-0836.pdf

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14 Chapter 14 Genetic resistance toviruses in tomato

1 Introduction

Plant viruses can drastically abate crop yields as theeffects of the disease inflicted by them

is getting more severe worldwide. Therefore, plant virusmanagement has always been

one of the main objectives of crop cultivation andimprovement programmes. Although it

is very difficult to give a clear figure on the financialimpact of plant viruses in agriculture,

the worldwide yield losses that can be ascribed to plantviruses are estimated to be more

than $30 billion annually (Sastry, 2014).

Genetic resistance in the host plant is considered highlyeffective in the defence against

viral infection. This is particularly true for thoseviruses that have prolific vectors which can

rapidly produce very large populations that are hard tocontain. Genetic resistance requires

neither the application of environmentally hazardouschemicals nor plant seclusion, and

the development of efficient and durable resistances ableto withstand the extreme

genetic plasticity of viruses, therefore, represents amajor challenge for the coming years.

A disadvantage, however, is that genetic resistancerequires the identification of resistance

loci which are not always available, and in many cases areidentified in wild species.

Inter-specific crossing programmes required for theintrogression of resistance from wild

species into the cultivated crop can be lengthy and

laborious.

The advances made in recent years in the sequencing ofwhole-plant genomes have made

the task of gene identification much easier, enabling thedevelopment of recombination

free precision DNA markers. These whole-plant genomesequences are also invaluable in

hastening the recovery of the susceptible recipient genomeduring backcross breeding

programmes designed to introgress genes of interest,including disease resistance genes

(genomic selection).

Over the past 80 years, great advances have been made onour understanding of plant

resistance against viruses (Nicaise, 2014). Approximatelyhalf of the known plant virus

resistance genes are dominant and encode for proteinscontaining a series of leucine-rich

repeats (LRRs), a nucleotide-binding site (NBS) and aputative amino-terminal signalling

domain (Belkhadir, 2004). They are, therefore, termedNBS-LRR proteins. These proteins

specifically recognize the viral avirulence (avr) geneproducts through the establishment of

the so-called ‘gene-for-gene’ interaction (Soosaar, 2004;Moffett, 2009; de Ronde, 2014).

In the last decade, a large number of crop recessiveresistance genes were also identified.

These resistances are often achieved through the absence ofappropriate host factors

that are required for the virus to complete its replicationcycle, emphasizing another

strategy to block viruses (Nicaise, 2014). In addition, the

discovery of RNA interference

pathways highlighted a very efficient antiviral systemtargeting the infectious agent at the

nucleic acid level (Bologna, 2014). Because plant virusesevolve and at times acquire the

ability to overcome the resistances employed by breeders,the development of efficient

and durable resistances able to withstand the geneticplasticity of viruses, therefore, still

represents a major challenge (Nicaise, 2014).

This section will cover selected achievements and concernsin resistance-breeding to

three major viruses that are of main concern in tomato(Solanum lycopersicum L.) breeding

and cultivation: tomato yellow leaf curl virus (TYLCV),tomato mosaic virus (ToMV) and

tomato spotted wilt virus (TSWV). These include issuesessential for the development of

resistance, such as the development of controlledprocedures for inoculation, optimal

plant age for resistance screening, and more.

2 Case study 1: Resistance to TYLCV

TYLCV, a monopartite begomovirus (family Geminiviridae), isone of the most devastating

viruses in tomatoes in many tropical and subtropicalregions worldwide (Lapidot, 2002;

Navas-Castillo, 2011, Lapidot, 2014). Like allbegomoviruses, TYLCV is transmitted by the

whitefly Bemisia tabaci in a circulative and persistentmanner (Cohen, 1964; Rubinstein,

1997).

The viral circular ssDNA genome of nearly 2.8 kb contains

six open reading frames

(ORFs) that are organized directionally, two in the senseorientation and four in the

complementary orientation (Gafni, 2003; Gronenborn, 2007;Lapidot, 2006; Fondong,

2013). The bidirectional ORFs are separated by a ~250-bpintergenic region (IR) that

contains elements for replication and bidirectionaltranscription (Gutierrez, 1999;

Gronenborn, 2007; Hanley-Bowdoin, 1989; Petty, 1988).

On the complementary strand, the C1 gene encodes Rep(replication-associated

protein) which is a multifunctional protein involved inviral replication and transcriptional

regulation. This is the only viral protein that isunreservedly required for viral replication

(Gronenborn, 2007). The C2 gene encodes TrAP(transcriptional activator protein),

which enhances expression of the coat protein, and plays arole in the suppression of

host defence responses as well as in viral systemicinfection (Bisaro, 2006; Brough, 1992;

Etessami, 1991). The C3 gene encodes the REn (replicationenhancer protein) which acts by

enhancing viral DNA accumulation in infected plants andinteracts with Rep (Sunter, 1990).

The C4 gene which is embedded within the C1 gene, but in adifferent ORF, is implicated

in viral pathogenicity and movement (Jupin, 1994; Ridgen,1994).

On the sense strand, the capsid protein (CP) encoded by V1is required for whitefly

transmission, binds to viral ssDNA, may play a role in

systemic movement and acts as

a nuclear shuttle protein that mediates movement of viralnucleic acid into the host cell

nucleus (Azzam, 1994; Briddon, 1990; Kunik, 1998;Palanichelvam, 1998; Rojas, 2001).

The product of the V2 ORF is involved in viral movement(Rojas, 2001; Wartig, 1997) and

has been shown to act as a suppressor of RNA silencing(Zrachya, 2007).

TYLCV induces severe yield losses in tomato which,depending on the age of the plant

at the time of infection, can reach 100% (Lapidot, 1997;Levy, 2008). Two to three weeks

after inoculation, the infected tomato plant displayspronounced disease symptoms that

include upward cupping of the leaves, chlorosis of the leafmargins and severe stunting

of the entire plant (Fig. 1). In many tomato-growing areas,TYLCV has become the

limiting factor for the production of both open-field andprotected cultivation systems

(Lapidot, 2002).

TYLCV was first detected and identified in northern Israel,following an outbreak of a new

disease in tomatoes in 1959 (Cohen, 1964, 2007). Similardisease symptoms associated

with high populations of whiteflies were observed intomatoes grown in the Jordan Valley

during the late 1930s (Avidov, 1946). The outbreaks oftomato yellow leaf curl disease

(TYLCD), which were sporadic in the 1960s, became a seriouseconomic problem and, by

end of the 1970s, all tomato-growing regions in the eastern

Mediterranean Basin were

affected by TYLCD (Hanssen, 2012). In the late 1980s, TYLCVparticles were isolated and

the virus was cloned and sequenced (GenBank accession no.X15656), and found to be a

monopartite begomovirus (Navot, 1991). Shortly thereafter,another Mediterranean viral

strain inducing TYLCD was cloned and sequenced – tomatoyellow leaf curl Sardinia virus

(TYLCSV; GenBank accession no. X61153) (Kheyr-Pour, 1991).Over the years, especially

Figure 1 Comparison of TYLCV-resistant and susceptiblelines in the field. TYLCV-resistant and

-susceptible lines were compared under field conditions.The different lines were transplanted in

alternating rows. The front row shows a susceptible lineexpressing severe TYLCV symptoms, while the

second row shows a resistant line not showing any diseasesymptoms.

with the advent of sequencing as a routine procedure, itbecame apparent that the name

TYLCV had been given to a heterogeneous group of more thanten virus species and

their strains, all of which induce very similar diseasesymptoms in tomato (Moriones, 2000;

Navas-Castillo, 2011).

TYLCV, which most probably emerged from the easternMediterranean, spread

westward and became recognized as a tomato pathogenthroughout the Mediterranean

Basin (Czosnek, 1977; Cohen, 2007; Hanssen, 2010, 2012;Lefeuvre, 2010; Navas-Castillo,

2011). The disease continued to spread westward into the

Caribbean, Central and

North America, and eastward towards China, Japan andAustralia. Today, it is present in

most tomato-growing areas worldwide (Lefeuvre, 2010;Navas-Castillo, 2011).

To succeed in a breeding programme designed to developresistant cultivars to the

virus, or any other pathogen for that matter, one mustdevelop an accurate and reliable

mass inoculation and selection system (Lapidot, 2006;Polston, 2013). Since many of the

whitefly-transmitted viruses are only poorly, if at all,mechanically transmitted, it is essential

to develop whitefly-mediated inoculation protocols, whichwill ensure high infection rates

(preferably 100%) and a standardized inoculum pressure (fora review, see Lapidot, 2007).

Relying on spontaneous field infection has been shown to belargely inefficient, as many

plants escape infection, even under heavy inoculationpressure (Vidavsky, 1998), probably

due to either/or: (1) low percentage of viruliferouswhiteflies in the general whitefly

population in the field (Cohen, 1988), (2) late andunsynchronized infection (Pico, 1998)

and (3) mixed infections with other viruses or pathogensthat may result in resistant plants

erroneously considered susceptible.

There have been prolonged efforts to breed tomato cultivarsresistant to TYLCV. Since

all cultivated tomato accessions were found to besusceptible to the virus, breeding

programmes have been based on the introgression of

resistance genes from accessions

of wild origin into the cultivated tomato (Ji, 2007b,Lapidot, 2002, 2006; Vidavsky, 2007).

Progress in breeding for TYLCV resistance has been slow,mainly due to the complex

genetic inheritance of the resistance, interspecificbarriers between wild and cultivated

tomato accessions, and the need for a reliable screeningprocedure for resistance to

the virus (Ji, 2007b; Lapidot, 2007; Vidavsky, 2007). Inspite of these challenges, TYLCV

resistant tomato cultivars are currently commercialized byseveral seed companies.

Sources of resistance to TYLCV have been identified andintrogressed from several wild

tomato species, including Solanum (S.) pimpinellifolium, S.peruvianum, S. chilense and

S. habrochaites. Until now six resistance loci, termedTy-1-through-Ty-4, ty-5 and Ty-6,

have been characterized and mapped to the tomato genomeusing molecular DNA

markers (Ji, 2007b; Hutton, 2014).

Resistance introgressed from S. chilense accession LA1969was found to be controlled

by a major partial dominant gene, termed Ty-1, and at leasttwo additional modifier genes

(Zamir, 1994). Ty-1 was mapped to the top of chromosome 6,while the two modifiers were

mapped to chromosomes 3 and 7 (Zamir, 1994). To the best ofour knowledge, Ty-1 is the

most exploited TYLCV-resistance locus in tomato breedingprogrammes worldwide, and

most of the commercial TYLCV-resistant hybrids available

today carry this locus.

Hanson (2000) analysed the resistant line H24, whichcontains resistance introgressed

from accession B6013 of S. habrochaites (Kalloo, 1990). Theauthors screened resistant

plants using what at the time they thought were threedifferent isolates of TYLCV. It was,

however, later found that those viral isolates were in factthree isolates of tomato leaf

curl virus (ToLCV) and not TYLCV. The resistance that wasfound to be dominant was

mapped to the bottom of chromosome 11, and was termed Ty-2(Hanson, 2006). Fine

tune mapping of Ty-2 was lately performed in order toidentify the gene controlling

resistance at this locus. However, because of severerecombination suppression in this

region, two candidate genes that may play a role in theTy-2-conferred resistance were

identified: a DNA-directed RNA polymerase II and atranscription factor of the MADS-box

family (Yang, 2014).

A major partially dominant resistance locus, which wasintrogressed from the S. chilense

accessions LA2779 and LA1932, was mapped to chromosome 6and was termed Ty-3

(Ji, 2006, 2007a). Based on DNA markers, the introgressionderived from LA2779 was

found to contain Ty-1 as well, suggesting either a linkagebetween Ty-1 and Ty-3 or that

Ty-1 and Ty-3 are allelic (Ji, 2007a). Two further studiesindeed established that Ty-1 and

Ty-3 represent two alternative alleles of the gene coding a

DFDGD-class RNA-dependent

RNA polymerase (DFDGD-RDRP; Verlaan, 2011, 2013),suggesting that the resistance

induced by these two alleles is via RNA silencing. A recentstudy (Butterbach, 2014)

confirmed this suggestion, showing the following: (1) UponTYLCV inoculation of resistant

lines carrying Ty-1 or Ty-3, low virus titre were detectedconcomitant with the production

of relatively high levels of siRNAs, whereas susceptibletomato revealed higher virus titres

but lower amounts of siRNAs. (2) Comparative analysis ofthe spatial genomic siRNA

distribution showed a consistent and subtle enrichment forsiRNAs derived from the V1

and C3 genes in Ty-1 and Ty-3 plants and (3) a relativehyper-methylation of the TYLCV V1

promoter region was observed in genomic DNA extracted fromTy-1 plants compared with

that from their susceptible counterparts.

Ty-4 was introgressed from S. chilense LA1932 and has beenmapped to the long arm

of chromosome 3. This locus is considered to be a minor onebecause it only accounted

for 16% of the resistance variation, while Ty-1 and Ty-3usually account for nearly 50% of

that variation (Ji, 2009).

The TYLCV-resistant line TY172, carrying ty-5, is thoughtto be derived from four

different accessions formerly assigned as S. peruvianum:PI126926, PI126930, PI390681

and LA0441 (Friedmann, 1998). LA0441 was latersubclassified as S. arcanum (Peralta,

2005). TY172 is highly resistant to TYLCV: (1) it producesminimal symptoms following

infection (the resistant line depicted in Fig. 1 wasdeveloped from line TY172), (2) allows

only low levels of viral DNA accumulation and (3) exhibitedthe highest level of resistance

in a field trial designed to compare yield components ofselected resistant accessions

following inoculation with TYLCV (Friedmann, 1998; Lapidot,1997). Classical genetic

studies have suggested that the resistance in TY172 iscontrolled by three genes exerting a

partially dominant effect (Friedmann, 1998). Gene mappingshowed that the resistance in

TY172 was controlled by a previously unknown majorrecessive QTL and by four additional

minor QTLs (Anbinder, 2009). The major QTL was mapped tochromosome 4 and was

designated ty-5. The gene controlling resistance at thety-5 was recently identified as

Messenger RNA Surveillance Factor Pelota, implicated in theribosome recycling phase of

protein synthesis (Lapidot, 2015).

The recessive resistance in the old commercial cultivar‘Tyking’ (Royal Sluis,

The Netherlands) has been shown to co-localize with theresistance in TY172 (Hutton,

2012). Resistance derived from this cultivar has been usedin many breeding programmes.

Interestingly, Bian (2007) determined that resistance inthe tomato line Fla. 653 was

controlled by a recessive allele termed tgr-1. Fla. 653 hasresistance derived from

‘Tyking’ and is homozygous for ty-5 (Hutton, 2012). Inanother study, Giordano (2005)

also identified a recessive allele (termed tcm-1) derivedfrom ‘Tyking’, which was effective

against bipartite begomoviruses. Hence, Hutton (2012)hypothesized that tgr-1 and

tcm-1 both represents the ty-5 allele from ‘Tyking’, andspeculated that this allele was

introgressed from S. peruvianum.

Ty-6 was introgressed from S. chilense LA1938 and has beenmapped to chromosome

10 (Hutton, 2014). Interestingly, a recent study showedthat Ty-6 in combination with either

Ty-3 or ty-5 strongly controls resistance to both TYLCV andanother bipartite begomovirus

tomato mottle virus (ToMoV) (Scott, 2015). These findingsillustrate the advantage of

pyramiding several Ty resistance genes into a single tomatocultivar to increase both

resistance spectrum and strength and suggest thatcombinations of Ty resistance genes

generally provide more effective control againstbegomoviruses than do single genes

(Hutton, 2015).

3 Case Study 2: Resistance to Tobamoviruses

ToMV, which belongs to the genus Tobamovirus (familyVirgaviridae), has a genome

composed of a single positive sense RNA molecule, nearly6400 nucleotides long. The

viral RNA codes for at least four proteins: (1) twooverlapping 126 and 183 kDa replication

proteins which are translated directly from the viral RNA,

and are part of the viral replication

complex; (2) a 30 kDa movement protein (MP), which isrequired for viral cell-to-cell

movement; and (3) the 17.5 kDa capsid protein (CP) whichencapsidates the viral RNA and

is also involved in long-distance movement within the host.Both the MP and the CP are

expressed from individual subgenomic mRNAs (Knap, 2001).

Historically, different tobamoviruses causing variousdiseases were all designated strains

of tobacco mosaic virus (ToMV), the type member of thetobamovirus genus. Thus, many

viruses originally referred to as ToMV strains are nowrecognized as a separate species.

Hence, ToMV, which is ~80% identical to ToMV at thenucleotide sequence level, was

referred to either as ToMV or as the tomato strain of ToMV.One criterion for distinguishing

the members of separate tobamovirus species is a nucleotidesequence difference of at

least 10% (Lewandowski, 2008).

The viral RNA genome is encapsidated by over 2000 units ofthe CP, thus creating a

rod-shaped virion particle of approximately 300 nm long and18 nm in diameter. This

rod-shaped virion is exceptionally stable, making ToMV (aswell as other tobamoviruses)

extremely persistent. ToMV can survive in leaf and rootdebris for long periods of time,

depending on environmental conditions – soil temperatureand whether it is dry or moist.

ToMV-infected leaf debris remained infective for over twoyears in dry soil and can persist

in infected root debris for even longer periods of time.Infectious ToMV particles were also

isolated from fresh and seawater, fog and clouds, surviveda short exposure in space, and

the virus was even detected in ancient glacial ice(Castello, 1999).

The virus has no insect vector and is transmittedmechanically (sap transmitted) as

well as by means of seeds. ToMV is very easily transmittedwhen an infected leaf rubs

against a leaf of a healthy plant, by contaminated tools,and by workers handling the

plants, especially in greenhouse-grown tomatoes.Transplanting tomato seedlings to

ToMV-contaminated soil can also result in infection. Thevirus can also contaminate seed

coats, and the plants germinating from these seeds canbecome infected, especially

during transplanting. ToMV infects tomato plantssystemically, causing mosaic symptoms

– leaves of infected plants are characterized byintermingled light and dark green mottle

regions, with rough downturned edges (a tomato leafexpressing ‘classical’ ToMV disease

symptoms is shown in Fig. 2). Plant growth may be stunted,with poor fruit set and small,

brown-streaked fruit (Panthee, 2013). ToMV’s effect ontomato yield is twofold – infected

plants produce less yield and in many cases the yieldproduced is of poor quality and is

not suitable for marketing. The virus is spread worldwideand affects mainly greenhouse

grown tomatoes. Prior to the development of resistance,

ToMV-induced yield loss was

estimated to be about 20% of the tomato production(Broadbebt, 1976).

Two resistance genes, Tm-1 and Tm-2, conferring resistanceagainst ToMV have been

introgressed to cultivated tomatoes. The Tm-1 gene, whichdisplays a semi-dominant

inheritance, was originally identified from S. habrochites‘PI126445’ (Pelham, 1966;

Watanabe, 1987). Tm-1 maps to the tomato chromosome 2 andencodes a ~80 kDa protein

that physically binds to and functionally inhibits thereplication proteins of ToMV (Ishibashi,

2007). This mode of action indicates that Tm-1 hascharacteristics different from those of

previously identified virus resistance genes in plants.This complements the fact that the

Tm-1 protein does not share any functional domain withknown resistance (R) proteins

(Ishibashi, 2007).

The Tm-2 resistance gene was characterized in S. peruvianumand found to confer a

higher level of resistance compared to that displayed byTm-1. The gene maps to the long

arm of the tomato chromosome 2 and harbours two resistantalleles: Tm-2 and the Tm-2 2

(Pelham, 1966; Young, 1989), with Tm-2 2 being moredurable than Tm-2 (Fraser, 1990).

Consequently, Tm-2 2 is both practically and economicallymore important and has thus

been widely employed as a ToMV resistance source in tomatobreeding programmes.

Both Tm-2 and Tm-2 2 are dominant and encode a member of

the CC-NBS-LRR class of

resistance proteins (Lanfermeijer, 2003). The Tm-2 2 andTm-2 ORFs only differ by seven

nucleotides, resulting in four amino acid differences atthe protein level. Two of these

differences are located in the nucleotide-binding site, andthe other two are located in the

LRR domain (Lanfermeijer, 2005).

Tm-2 and Tm-2 2 are associated with a plant’s resistanceresponse known as hypersensitive

(HR). HR, induced by specific recognition of the invadingvirus, localizes virus spread by

rapid programmed cell death surrounding the infection site,and typically results in visible

necrotic local lesions. HR-mediated resistance is a commonresistance mechanism for

Figure 2 ToMV-induced disease symptoms. A close-up of aninfected tomato plant showing typical

intermingled light and dark green mottle regions (left) anda leaf of a non-infected plant (right).

viruses and for other plant pathogens. Analysis of thenucleotide sequence of resistance

breaking virus isolates indicated that the MP protein isthe avirulence factor in this

resistance system (Calder, 1992; Weber, 1993).

Comparison of the two resistance-conferring alleles (Tm-2and Tm-2 2 ) with two susceptible

alleles allowed discussion of the structure–functionrelationship in the Tm-2 proteins.

It is proposed that the Tm-2 proteins display apartitioning of the leucine-rich repeat

domain, in which the N-terminal and C-terminal partsfunction in signal transduction and

MP recognition, respectively (Lanfermeijer, 2005).

Tm-2 2 is the most widely deployed ToMV-resistance inbreeding programmes as it

confers resistance to most of the strains of the virus, andwas stable and effective for over

40 years. Hence, most, if not all, commercial tomatohybrids today carry this resistance.

Recently, two new emerging tobamoviruses which overcome theTm-2 2 resistance were

identified.

Tomato mottle mosaic virus (ToMMV): The virus was firstidentified in a greenhouse

tomato sample collected in Mexico in 2013 (Li, 2013). Thevirus continued to spread and

was reported to infect tomatoes in Florida, New York andvery recently in Israel and Spain

(Webster, 2014; Padmanabhan, 2015; Ambros, 2016; Turina,2016). This virus was also

reported to infect pepper plants in China (Li, 2014). Thevirus is closely related to ToMV,

with 85% nucleotide sequence identity. Based on sequencesimilarity analysis, this virus

is likely present in Brazil (GenBank accession numberAF411922) and Iran (HQ593616) as

well. The virus induces the classical tobamovirus symptomsof mosaic and leaf distortion,

Figure 3 A ToMV-resistant commercial tomato hybrid showingToBRFV-induced systemic symptoms.

A greenhouse tomato hybrid showing systemic ToBRFV diseasesymptom, including leaf mosaic,

mottling, elongation and deformation (left), as well as asevere brown rugose symptoms on the fruit

(right). Photos are courtesy of Dr. David Levy, HazeraSeeds, Israel.

accompanied at times with a rapid tissue necrosis. Ling(2016) reported that the virus was

able to systemically infect a tomato cultivar that isToMV-resistant.

Tomato brown rugose fruit virus (ToBRFV): In 2015, acommercial tomato hybrid

(cv. ‘Candela’) grown in greenhouses in Jordan showed mildfoliar symptoms at the end

of the season accompanied with strong brown rugose symptomson fruits (Salem, 2015).

The causal agent was found to be transmitted mechanicallyto test plants, and the plants

were tested positive for tobamovirus infection. The viruswas cloned and sequenced,

identified as a new tobamovirus and tentatively namedToBRFV. Following sequence

comparisons with other tomato-infecting tobamoviruses, thenew virus had the highest

nucleotide sequence identity (82.4%) with the Ohio V strainof ToMV. ToBRFV was recently

identified in greenhouse tomatoes in the south of Israel(A. Dombrovsky, pers.comm.). The

virus was identified on a number of different commercialtomato hybrids, all of which are

ToMV-resistant. Figure 3 shows ToBRV-induced symptoms onToMV-resistant greenhouse

grown commercial tomato hybrids. Symptoms include leafmosaic, mottling, elongation

and deformation, as well as severe brown rugose symptoms onthe fruit, making the fruit

unsuitable for marketing.

These two new emerging tobamoviruses which overcome theTm-2 2 resistance

demonstrate the genetic plasticity of viruses in theirinteraction with resistance genes. This

exemplifies the need for the continuous development of new,more efficient and durable

resistances able to withstand a wider range of virusstrains.

4 Case study 3: Resistance to TSWV

TSWV is the type species of the genus Tospovirus, the onlyplant virus genus within the

Bunyaviridae, a large viral family containing primarilyarthropod-borne viruses (Papu,

2008; Hanssen, 2012; Turina, 2016). The virus genome issegmented and composed

of three single-stranded RNA molecules designated L, M andS according to their size

(large, medium and small, respectively). The negative senseL RNA is ~8.9 Kbp and codes

for the viral RNA-dependent RNA polymerase (RdRp) protein.Both the M and S RNAs

are ambisense in their genome organization. The M RNA is~4.8 Kbp and codes for the

precursors of two membrane structural glycoproteins, G Nand G C , and a nonstructural

protein, the cell-to-cell movement protein, NSm. The S RNAis ~2.9 Kbp and codes for

the nonstructural protein NSs, which acts as a suppressorof RNA silencing and for the

nucleocapsid protein (N) (Kormelink, 2011).

The three genomic RNAs are tightly linked with the Nprotein forming ribonucleoproteins

(RNPs). These RNPs are encased within a lipid envelope

consisting of two virus-encoded

glycoproteins (Gn and Gc) that form spikes on the surfaceand are required for virus

acquisition and transmission by thrips vectors. The virusparticles are spherical and

surrounded by a host-derived membrane with a diameter of80–120 nm. Due to the

negative sense of the L RNA, virus particles containseveral molecules of the RdRp to

initiate rounds of replication of the viral RNAs. Genomeexpression is facilitated through a

synthesis of subgenomic RNAs (Papu, 2008; Turina, 2016).

In nature, TSWV is transmitted by a limited number ofthrips species in a persistent,

circulative and propagative manner. The western flowerthrips, Frankliniella occidentalis,

is the most efficient vector of the virus. Under laboratoryconditions the virus can also be

efficiently transmitted mechanically. Tospoviruses are notseed transmitted. Although adult

thrips are able to transmit the virus, only the immaturelarva (first and second instar larva) is

capable of acquiring the virus by feeding on an infectedplant. The virus starts replicating

in the larva and survives through the developmental stages.The emerging adult transmits

the virus and continues so for the lifespan of the insect.Hence, tospoviruses are capable of

replicating in both their host plants and thrips vectors(Hogenhout, 2008; Whitfield, 2005).

TSWV-induced disease symptoms in tomato can range from mildto severe, depending

on the tomato genotype, the viral isolate, the

developmental stage of the plant and the

environmental conditions (Hanssen, 2012). Leaf symptomsconsist of purpling on the lower

leaf surface and yellowing combined with small necroticspots that develop into the typical

bronzing on the upper leaves. Tomato fruit sometimesdisplays concentric rings that vary

in colour depending on the ripening stage, andoccasionally, circular necrotic spots or

even general fruit necrosis can occur on the fruit surface(Fig. 4) (Hanssen, 2012).

Sources that are resistant to Tospoviruses have been foundin diverse cultivars of

S. lycopersicum and several accessions of wild tomatospecies, including S. habrochaites,

S. peruvianum, S. chilense and S. pimpinellifolium(Rosello, 1998; Stevens, 2003; Soler,

2003; Saidi, 2008; Gordillo, 2008; Riley, 2011; Sohrab,2014). To date, five dominant

(Sw-1a, Sw-1b, Sw-5, Sw-6 and Sw-7) and three recessive(sw-2, sw-3 and sw-4)

TSWV resistance genes have been reported (Lee et al.,2015). Among these, the recessive

(sw-2, sw-3 and sw-4) and dominant allelic (Sw-1a andSw-1b) genes have not been widely

utilized in breeding programmes due to their strainspecificity (Finlay, 1953; Price, 2007;

Stevens, 2007; Saidi, 2008; Turina, 2016). It was foundthat it would be necessary to

pyramid the three recessive genes together with any of thetwo Sw-1 alleles in a single

genotype in order to obtain wide protection. This complexgenetic configuration restricts

Figure 4 TSWV-infected tomato plants. Greenhouse tomatoplants showing systemic symptoms of

TSWV (left) and chlorotic spots on fruits (right). Photosare courtesy of Dr. David Levy, Hazera Seeds,

Israel.

the development of hybrids considerably (Rosello, 2001).For the dominant genes denoted

Sw-6 and Sw-7, partial resistance to a narrow range of TSWVisolates has been observed

(Rosello, 1998, 2001). Probably because of theirinsufficient resistance spectrum these

reported resistance genes have not been thoroughlycharacterized at the molecular level.

Thus, it is not entirely clear whether they representdifferent genes located on distinct

chromosomes or represent different alleles from awell-known resistance gene cluster

(Turina, 2016). The exception is the Sw-5 gene cluster, ofwhich many homologs have been

sequenced. This gene cluster originates from Solanumperuvianum and has been the most

widely deployed resistance source against TSWV because ofits durability and the ability

to provide stable resistance against virus species andisolates from different geographic

locations (Stevens, 1992, 1994, 1995; Rosello, 1998).Although the Sw-5 gene cluster was

cloned and characterized in 2001 (Spassova, 2001), onlyrecently molecular markers that

can assist in breeding have been reported (Dianese, 2010;Shi, 2011; Lee, 2015).

The Sw-5 gene is located on the telomeric region of thelong arm of chromosome 9

(Stevens, 1991, 1992, 1995; Chagué, 1996). The gene hasbeen introgressed into the fresh

market tomato cultivar Stevens (Stevens, 1964, 1992) and isshown to provide resistance

not only to TSWV but also to related tospoviruses likegroundnut ring spot virus (GRSV),

tomato chlorotic spot virus (TCSV), Chrysanthemum stemnecrosis virus (CSNV), and to the

less related Impatiens necrotic spot virus (INSV) (Boiteux,1993; Spassova, 2001; Dianese,

2011; Hallwass, 2014). All these different tospovirusspecies are phylogenetically related

and present within a putative American clade (Pappu, 2009;Turina, 2016).

The Sw-5 gene was cloned and found to be situated within acluster of five paralogs,

named Sw-5a-through-Sw-5e (Spassova, 2001). Of these, onlythe Sw-5b copy has been

proven to be functional and sufficient for a broad-spectrumresistance against tospoviruses

(Hallwass, 2014; Peiró, 2014; Spassova, 2001). The gene isa member of the coiled coil,

nucleotide binding, leucine-rich repeat (CC-NBS-LRR) classof plant resistance genes.

The gene significantly resembles the tomato nematode andaphid resistance gene Mi

and, to a lesser extent, Pseudomonas syringae resistancegene Prf.

5 Summary and future trends

Genetic resistance to plant viruses represents anenvironmentally safe strategy to combat

the substantial losses in yield and product qualityinflicted by them. These losses are

becoming more severe in recent years and are attributedmainly to the genetic plasticity of

viruses and also to global warming, known to modulate theresponse of resistant plants to

viruses. Therefore, the search for new and novel geneticstrategies to render susceptible

plants resistant to viruses remains a major challenge inthe coming years as well.

The advances made in recent years in the high-throughputsequencing and re-sequencing

of whole-plant genomes have made the task of geneidentification much easier, enabling

fast identification of genes that control resistance andthe development of recombination

free precision DNA markers. These whole-plant genometechnologies are also invaluable

in hastening the recovery, or capturing, the elitesusceptible recipient genomes during

backcross breeding programmes designed to introgress genesof interest, including

disease resistance genes (genomic selection). Thesetechnologies will cumulatively

enhance the pyramiding of genes into elite commercialhybrid, an approach which will

become more commonplace in the upcoming years.

The advances made in recent years in genome editingtechnologies, such as CRISPR

Cas (Belhaj, 2015), are expected to revolutionize andsubstantially hasten the breeding

of resistant cultivars (Chandrasekaran, 2016). The majoradvantage of these technologies

is that they permit direct engineering of genes withoutleaving GMO traces in the final

genotype (Xu, 2015) and thus eliminate the laborious andtime-consuming process of

backcross breeding. Although these technologies arecurrently restricted to phenotypes

controlled by recessive genes, it is anticipated that theycould potentially be implemented

to dominant genes as well.

6 Acknowledgements

We thank Dr. David Levy, Hazera Seeds, for his contributionto Fig. 3 and 4. We also

thank Dr. Aviv Dombrovsky, Institute of Plant Protection,Volcani Center, ARO, for sharing

with us his findings regarding the spread of ToBRFV inIsrael. Part of the knowledge we

present in this chapter was made available throughfinancial support provided by the

chief scientist of the Israeli Ministry of Agriculture andRural Development (No. 261-1159)

and by Israel Binational Agricultural Research andDevelopment Fund (No. IS-4409).

Contribution no. 72017 from the Agricultural ResearchOrganization, Volcani Center, Bet

Dagan, Israel.


For those interested in more information regarding viralresistance in tomato or in vegetable

crops, a good place to start will be the ‘Advances in VirusResearch’ series which covers

a diverse range of in-depth reviews providing a valuableoverview of the current field of

virology. Some of the books in this series are dedicated toa specific topic, for instance

volumes 75 and 76 (2009 and 2010, respectively) arededicated to ‘Natural and Engineered

Resistance to Plant Viruses’, Vol 84 (2012) ‘Viruses andVirus Diseases of Vegetables in the

Mediterranean Basin’ and Vol 90 (2014) ‘Control of PlantVirus Diseases: Seed-Propagated

Crops’. The series contents can be viewed on ScienceDirectat http://www.sciencedirect.

com/science/bookseries/00653527/94. A recommended textbookwill be Plant Virus-Host

Interactions, Molecular Approaches and Viral Evolution,edited by R. K. Gaur, T. Hohn and

P. Sharma, published in 2014 by Academic Press.

The Tomato Genetics Cooperative (TGC), initiated in 1951,is a group of researchers who

share their interest in tomato genetics, and who haveorganized informally for the purpose

of exchanging information, germplasm and genetic stocks.The Report of the Tomato

Genetics Cooperative is published annually and containsreports of work in progress by

members, announcements and updates on linkage maps andmaterials available. The TGC

site (http://tgc.ifas.ufl.edu/index.htm) also includesother tomato links.

The Tomato Breeders Roundtable (TBRT) has been the premiermeeting in North America

for and scientists interested in tomato improvement and itattracts researchers from around

the world. TBRT meets every 18 months, usually in theUnited States. Information about

the meetings as well as presentations and abstracts can befound at the TBRT site (http://

tgc.ifas.ufl.edu/TBRTMeetings.htm).

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15 Chapter 15 Bio-ecology of major insectand mite pests of tomato crops in thetropics

1 Introduction

Tomato (Solanum lycopersicum L.) is one of the mostimportant vegetables in the world.

On an average, it is grown on more than 4.50 million hawith an annual production of

nearly 163 million tonnes. Asia and Africa account forabout 67% of the global tomato

production in the last decade (FAO, 2013). In the tropics,tomato production is severely

constrained by several insect- and mite pests. The majorpests include fruit borer, common

armyworm, beet armyworm, whitefly, thrips, aphid, leafminer and spider mites (Srinivasan,

2010). In the recent years, the South American tomato leafminer has become a serious

invasive pest in Africa, Mediterranean and parts of SouthAsia. Most of these insect pests

could lead to complete crop failure if left uncontrolled.However, they are partly triggered

to reach the economic injury level due to theindiscriminate use of broad-spectrum

chemical pesticides, which mostly eliminate the naturalenemy complex present in tomato

production systems in the tropics. Besides the naturalenemies, changes in the landscapes

and cropping systems, warming climate and so on also alterthe pest profiles including

their damage potential. Hence, it becomes imperative tounderstand the bio-ecology of

major insect and mite pests on tomato in the tropics, andthis chapter summarizes the

recent findings in this perspective.

2 Aphids

An aphid can become a serious pest of tomato in its earlyvegetative growth stage. Aphis

gossypii is commonly known as ‘cotton aphid’ or ‘melonaphid’, because of its preferential

feeding on Malvaceae, especially cotton, and Cucurbitaceae,especially melons. However,

this aphid is highly polyphagous, feeding on hundreds ofhost plants. Both the nymphs

and adults occur in large numbers on the tender shoots(Fig. 1), leaf surfaces, floral buds

and so on. They suck the plant sap from the tender plantparts, where they aggregate.

Damage symptoms include yellowing, leaf curl anddeformation. Severe feeding leads to

reduced vigour and stunted plant growth. Aphids alsoproduce honeydew (Fig. 2), which

Figure 1 Adult aphids on tomato shoot.

Figure 2 Honeydew of aphids on leaf surfaces.

leads to the development of sooty mould due to the growthof saprophytic fungi on leaf

surfaces and thus reducing the photosynthetic efficiencyand productivity of the plants.

In the tropics, aphids usually do not have sexualreproduction. They reproduce by

parthenogenesis, and are viviparous. The adult ispear-shaped and its colour is highly

variable from yellow to dark green. Mostly they are presentin wingless form, although

both wingless and winged forms are possible. Winged formsare present only under

high population density conditions, inferior host plantquality and so on. Aphids can

be easily identified by a pair of black-coloured cornicleson the dorsal side of their

abdomen. In general, aphid’s life cycle is about a week toten days depending on the

temperature and host plant quality. Studies confirmed theoccurrence of distinct biotypes

of A. gossypii (Guldemond et al., 1994). Although biotypesof the melon/cotton aphids

are morphologically indistinguishable, they have distincthost ranges. Subsequent studies

have shown some differences in host preference (Wang etal., 2004), feeding behaviour

and virus transmission (Yokomi et al., 2004; Gutierrez etal., 2008) between the melon and

cotton biotypes. Hence, genetically distinct biotypes seemto be common in A. gossypii.

Because of the honeydew production, aphid colony is usuallyattended by the ants, which

at times protect the aphids from their predators. Among thebiotic mortality factors, natural

enemies of A. gossypii play a vital role in the field. Forinstance, various species of ladybird

beetles such as Menochilus sp. and Coccinella sp. predatethem in the field. Similarly, different

parasitoids including Aphelinus sp., Lipolexis sp. andTryoxis sinensis parasitize the nymphs of

A. gossypii in the tropics (Herlinda et al., 2011). Hence,the natural enemy complex should be

monitored before pesticide spraying is scheduled to manageA. gossypii on tomato. Aphid

mostly occurs during the cool dry season. Relative humidity

is an important abiotic factor that

favours the aphid population growth (Chakraborty, 2011).Elevated carbon di oxide is found

to increase the fecundity of A. gossypii through successivegenerations (Chen et al., 2005). In

addition, A. gossypii is reported to feed more on plantsunder elevated carbon di oxide and

thus leading to reduced photosynthesis due to largeramounts of honeydew produced (Sun

et al., 2009). Thus, abiotic factors especially relativehumidity and carbon di oxide could alter

the developmental biology and damage potential of A.gossypii.

3 Thrips

Thrips palmi is widely distributed in South- and SoutheastAsia and Oceania. However,

spread and establishment of this species are limited byclimatic conditions (McDonald

et al., 1999). It could infest the crops under greenhousewidely, although it is a serious

pest in field conditions in the tropics. T. palmi ispolyphagous, and is known to feed on

various vegetables including Solanaceous and Cucurbitaceousvegetables. However, it

is commonly known as ‘melon thrips’ because of itspreferential feeding on cucurbits.

Although Scirtothrips dorsalis is predominantly present inAsia, it is also present in Africa

and Greater Caribbean (Kumar et al., 2014). It prefers tofeed on pepper, although it is

reported to damage tomato (Meena et al., 2005; Kaur et al.,2010) and cucumber (Kadirvel

et al., 2013). A recent study suggests that S. dorsalis as

a highly polyphagous pest with

a rapidly expanding global distribution may be comprised ofcryptic species. According

to this study, the cryptic species, South Asia 1 is highlyinvasive, polyphagous and likely

implicated in tospovirus transmission. Two other species,South Asia 2 and East Asia 1

are also highly polyphagous and appear to be at an earlierstage of global invasion. The

remaining members of the complex are regionally endemic,varying in their pest status

and degree of polyphagy (Dickey et al., 2015).

Thrips feed mostly on foliage mostly along the mid-rib andveins, but occasionally on

fruits. Damaged leaves (Fig. 3) show silvery feeding scarson the leaf surfaces, along the

mid-rib and veins. Severe infestations can lead to bronzingand drying of the leaf surfaces.

Infested fruit is usually scarred and/or deformed. Thripsalso transmits the tospovirus

diseases especially, tomato spotted wilt virus (TSWV) andpeanut bud necrosis virus (PBNV)

on tomato. It is important to note that these diseases canlead to complete crop failure

(Kunkalikar et al., 2011; Ramana et al., 2011).

T. palmi is usually yellow in colour. However, othertaxonomic characters should be

used to confirm this species. Otherwise, it could be easilyconfused with another yellow

coloured thrips species, T. flavus, or even the pale formof Frankliniella schultzei. The

head and legs of S. dorsalis are pale, with dark wings.Usually the female thrips insert the

eggs into the leaf tissues. Each female thrips lays about200 eggs. The nymph has two

active feeding stages, and the pupal stage also consists ofpre-pupa and pupa. The total

developmental time varies from two to three weeks. Theviruliferous thrips usually acquire

the virus when they are first instar or early secondinstar, to be the highly efficient vectors.

Thrips are favoured by warmer weather and hence they mostlyattack tomato during

the dry season. Also, warming weather could expand thegeographical distribution of

thrips over its current weather restrictions in thetemperate region(s) as predicted by a

study in Korea recently (Park et al., 2014). A eulophidparasitoid species, Ceranisus menes

(Walker), was found to be the natural enemy of T. palmi inThailand (Hirose et al., 1993) and

Japan (Hirose et al., 1992). Since this parasitoid specieshas a broader host range including

Frankliniella and Megalurothrips, and wider geographicaldistribution (Loomans, 2006), it

is expected to be a major mortality factor.

4 Whitefly

Whitefly is one of the most important insect pests oftomato, because of its damage

potential as a direct pest and the vector of virus diseasesin tomato. It is widely distributed

Figure 3 Thrips and their feeding damage on leaf surfaces.

in tropical and subtropical regions, and in greenhouses intemperate regions. Bemisia

tabaci is one of the highly polyphagous pest insects, and

is known to feed on several

agricultural as well as horticultural crops and weeds. Forinstance, a recent survey in China

recorded a total of 361 plant species from 89 families,especially Compositae, Cruciferae,

Cucurbitaceae, Solanaceae and Leguminosae as host species(Li et al., 2011). Worldwide,

it infests more than 900 different plant species undergreenhouse and field conditions

(Perring, 2001; Berry et al., 2004).

Adults (Fig. 4) and nymphs (Fig. 5) of B. tabaci suck theplant sap and reduce the vigour of

the plant. In severe infestations, the leaves turn yellowand drop off. When the populations

are exceedingly higher, they produce large quantities ofhoneydew, which would favour the

growth of sooty mould on leaf surfaces and thus reducingthe photosynthetic efficiency of

the plants. B. tabaci also acts as a vector for severalviral diseases including tomato yellow

leaf-curl virus (TYLCV). Plants infected by TYLCV (Fig. 6)show stunted growth with erect

shoots, curled leaflets, reduced leaf size and yellowingalong the margins of the leaves.

Figure 4 Whitefly (Bemisia tabaci) adults.

Figure 5 Red-eyed nymph of whitefly (Bemisia tabaci).

The flowers wither and droop, and hence the fruit set isreduced or nil. The onset of TYLCV

in early crop stages can lead to 100% yield loss.

Biotypes of the B. tabaci complex are morphologicallyindistinguishable (Rosell et al.,

1997), and these biotypes were reproductively incompatible

(Liu et al., 2007). More than

24 biotypes designated from A to T have been reportedearlier (Perring, 2001; Simon

et al., 2003; Zang et al., 2006) based on the capacity totransmit begomoviruses, capacity

to induce silver leafing in squash or yellow vein inhoneysuckle and nightshade, host

range and other characteristics (De Barro et al., 2011).Until recently, the term ‘biotype’

was used by most researchers in differentiating B. tabacipopulations (Tay et al., 2012).

However, Boykin et al. (2007) reported that the globalpopulation of B. tabaci consisted of

12 major genetic groups, based on a phylogenetic analysisof cytochrome c oxidase I gene

sequences. Subsequent studies showed that B. tabaci is acomplex of 11 well-defined

groups composed of at least 24 morphologicallyindistinguishable putative species

(Dinsdale et al., 2010; De Barro et al., 2011). Finally, arecent study has reported a total of

39 species in the B. tabaci complex (Alemandri et al.,2015).

Whitefly adult is a soft-bodied and moth-like fly. Thewings are held over the body

like a tent. The adult males are slightly smaller in sizethan the females. The females

mostly lay eggs near the veins on the underside of tomatoleaves. They prefer hairy leaf

surfaces to lay more eggs. Pear-shaped eggs are verticallyattached to the leaf surfaces

through a pedicel. Upon hatching, the first instar crawlermoves on the leaf surface to

locate a suitable feeding site. It will then insert itspiercing and sucking mouthpart and

starts sucking the plant sap from the phloem. The nymphsare flattened, oval-shaped and

greenish yellow in colour. The last nymphal stage has redeyes, which is sometimes known

as puparium (David, 2001). Adults emerge out from thesepuparia through a T-shaped slit.

B. tabaci is active during the day, and settles on lowerleaf surfaces at night. Hot, dry

conditions favour the whitefly, and heavy rain showersdrastically reduce population

build-up. Among the abiotic factors, temperature is animportant element in regulating

the B. tabaci population. Although the adult survivaldeclines only after 41°C (Cui et al.,

2008), the net reproductive success reduces at 33°C. Hence,Curnutte et al. (2014) found

that the optimal temperature for B. tabaci reproduction isbetween 28 and 33°C. It

should also be noted that female is more tolerant than maleto a higher temperature

Figure 6 Plants infected by tomato yellow leaf-curl virus(TYLCV).

(Cui et al., 2008). Natural enemies also adversely affectthe B. tabaci population in the

field. For instance, more than 100 species of parasitoidsand predators, and seven species

of entomopathogenic fungi were recorded in a survey inChina. Aphelinid parasitoids,

especially Encarsia and Eretmocerus genera were found to bethe dominant parasitoids of

B. tabaci in China (Li et al., 2011) as well othercountries in the tropics.

5 Leaf miner

Liriomyza bryoniae species occurs in Asia, Europe and NorthAfrica. L. bryoniae is a

polyphagous pest, although it prefers to feed onCucurbitaceae. The major host plants

include tomato, melons, cucumber, cabbage and lettuce.Besides L. bryoniae, L. sativae

(Blanchard), L. trifolii (Burgess) and L. huidobrensis(Blanchard) may also cause damages

to tomato. L. huidobrensis predominates at high elevations(over 1000 m above sea

level, ASL), whereas L. sativae colonizes on hosts in lowelevations (below 600 m ASL)

(Tantowijoyo and Hoffmann, 2011).

Although leaf miners can infest tomato since from theseedling stage, mostly the

infestation is limited to the early crop growth. In mostcountries in South- and Southeast

Asia, leaf miners may not attain the major pest statusunless the growers resort to the

application of broad-spectrum chemical pesticides, whichwould eliminate the natural

enemies early in the season. The larva usually feeds on theleaf mesophyll and causes

irregular mines on leaf surfaces. Severe damage is causedby the later larval stages. For

instance, the leaf area mined by the last larval instar isabout 88% of total infestation

(Cheng, 1994). In severe infestations, several mines areformed on the same leaf (Fig. 7),

which will drastically reduce the photosynthesis and thusreducing the yield.

L. bryoniae adult is a small, grey-coloured fly. Themesonotum is shiny black whereas the

legs are yellow and brownish. The females createoviposition punctures on leaf surfaces

and lay the eggs. Larva has three instars feeding insidethe leaf tissues. Larvae inside the

mines can be easily identified by their creamy yellowishcolour and sclerotized mouth

hooks. The larval period is about one to two weeks. Theoval-shaped pupa is shiny brown

Figure 7 Leaf miner infestation on tomato foliage.

in colour, and mostly found within the mine or on leafsurfaces. Pupal period is about 8–11

days (Parrella, 1987).

Available literature on the impact of abiotic factors orchanging climate on L. bryoniae

is scanty. However, some information is available on otherspecies of Liriomyza. A recent

study confirmed that L. trifolii which has been consideredthe dominant leaf miner species

in Kenya is gradually replaced by L. huidobrensis (Foba etal., 2015). It may be due to the

favourable effects of changing climate. For instance, L.sativae is displaced by the more

recent invader L. trifolii in warm climatic areas of China,because of the adaptation of

L. trifolii to a higher temperature (Wang et al., 2014).Natural enemies are an important

mortality factor against Liriomyza spp. A review on naturalenemies of Liriomyza has

identified approximately 140 species of parasitoids, a fewspecies of predators and

some entomopathogens (Liu et al., 2009). Diglyphus isaea is

a predominant parasitoid

of Liriomyza, and Beauveria bassiana, Paecilomyces spp.,Metarhizium anisopliae and

Verticillium lecanii are the major entomopathogens.

6 South American tomato leaf miner

Originated in South America, Tuta absoluta is a predominantpest of tomato in South

America. However, it got introduced into Europe in 2006.Since then, it has started

spreading as a devastative pest of tomato in Mediterranean,North Africa and more

recently in East Africa as well as South Asia (Tonnang etal., 2015). The origin of this

invading population was unique, and closer to or in Chile,and probably in Central Chile

near the town of Talca in the district of Maule (Guillemaudet al., 2015). Besides tomato,

it also infests crops such as eggplant, potato, pepper,nightshade, tobacco and common

bean (Ferracini et al., 2012).

The larvae feed on mesophyll and causes irregular mines(Fig. 8) on leaf surfaces.

However, these mines are broader than Liriomyza leaf mines,and pinkish larvae can be

easily found within the mines (Fig. 9). They make largegalleries and eventually tunnel

into the fruits (Fig. 10). Several larvae can feed inside asingle fruit and thus the fruits are

Figure 8 Irregular mines caused by Tuta absoluta feeding.

hollowed out quickly and rotten. The damage can lead to100% yield loss in open field

conditions as well as protected cultivation.

Small cylindrical eggs are usually laid singly on the lowerleaf surfaces, but occasionally

on floral buds, stems and calyx. The larva has fourinstars. Initially it is cream coloured

with dark head, and later it turns to green or pink.Brownish pupae are found in the soil

or on leaf surfaces inside the cocoon or at times withinthe leaf mines. Female moths

emerge one or two days earlier than the male moths in orderto mature reproductively

and produce pheromones. The sex pheromone contains(E,Z,Z)-3,8,11-tetradecatrienyl

acetate and (E,Z)-3,8-tetradecadienyl acetate (Attygalle etal., 1995; Svatos et al., 1996).

Small adults with filiform antennae have grey scales withcharacteristic black spots present

in anterior wings. Since the life cycle is completed withina month, up to 12 generations

can be found in warmer regions. Interestingly, laboratoryevidence of deuterotokous

parthenogenesis has been reported in T. absoluta in aFrench population for the first time

(Megido et al., 2012). Subsequently, it was also confirmedin three Tunisian populations

(Abbes and Chermiti, 2014).

Figure 9 Tuta absoluta larva within mines.

Figure 10 Tuta absoluta feeding damage on tomato fruit.

Due to T. absoluta occurrence in cold temperate and warmtropical regions, Tonnang

et al. (2015) presumed that T. absoluta is highly adaptedto wide range of temperatures,

which enabled the pest to thrive even in Northern Sudan

where the daily temperature may

occasionally reach up to 49°C in summer. Hence, theypredicted that a range expansion

in tropical Africa, parts of South-, East- and SoutheastAsia as well as the Pacific Island

countries with a reasonable upsurge of damage potential ispossible. Several natural

enemies, especially parasitoids have been recorded in itsnative range as well as invasive

regions of the world. The parasitoid species arepredominantly eulophid and braconid

wasps (Zappala et al., 2013). For example, the mostfrequent parasitoid species recovered

along the Mediterranean Spanish Coast were Necremnus sp.nr. artynes, Stenomesius cf.

japonicus and Neochrysocharis formosa (Hymenoptera:Eulophidae) (Gabarra et al., 2014).

7 Tomato fruit borer

The tomato fruit borer (Helicoverpa armigera) is apolyphagous and highly mobile insect.

It is a major pest on several agricultural andhorticultural crops as well as wild species. It

has been recorded as a damaging pest on more than 180cultivated and wild plant species

in at least 67 families (Czepak and Albernaz, 2013). It iswidely distributed in Asia, Africa,

Oceania and parts of Europe, with limited distribution inSouth America.

The neonate larvae feed on the leaf surfaces or floralbuds. However, the grown-up

larvae prefer to feed on the young fruits by making holesand thrusting their head inside

(Fig. 11). Hence the holes are circular (Fig. 12) and often

surrounded by the faecal pellets.

Later, the larva feeds most of the inner contents of thefruit and hollows-out. Severely

damaged fruits rot and fall down, or partially damagedfruits may become deformed.

Male moths are usually pale yellow with olive green whereasthe female moths are reddish

brown. Mostly, the female moths emerge first, and releasesex pheromones to attract

males. The sex pheromone is a multi-component system,although (Z)-11-hexadecenal was

reported as the major compound (Piccardi, 1977). The femalemoths lay eggs singly and

scattered, usually on or near the leaflets, floral buds oryoung fruit. They prefer to lay eggs

on the hairy surfaces of the plant. Maximum egg layingcoincides with the flowering phase

Figure 11 Feeding larvae of Helicoverpa armigera.

of the host plants. Each female can lay several hundredeggs, with a maximum of 4394

eggs (CABI, 2003). The neonate larvae are creamy white withdark brown or black-coloured

heads. The grown-up larvae vary in colour, from pale greento brown or even black with

lateral stripes on the body. The larva passes through sixinstars. If crowding occurs due to

high larval density, cannibalism can be observed among thegrown-up larvae. Pupation

takes place in soil. Pupae are dark brown. The pupae mayenter into diapause when larvae

are exposed to day lengths of about 11.5–12.5 hours, andlow temperatures (19–23°C),

or when larvae are exposed to lengthy periods of extremely

hot and dry weather (�35°C)

(King, 1994; Zhou et al., 2000; Shimizu and Fujisaki, 2002;CAB, 2003).

H. armigera is tolerant to high temperature. However,exposure of these adults to 40°C or

over for few hours could reduce the survival, mating andfecundity substantially (Mironidis

and Savopoulou-Soultani, 2010). H. armigera larvae feedingon elevated CO 2 -grown plants

are significantly smaller in size and highly vulnerable tothe predators (Coll and Hughes,

2008). Thus, warming temperature and increasing CO 2 mightadversely affect H. armigera

populations. Among the biotic factors, parasitoids andpathogens play a significant role in

regulating the H. armigera populations in open fieldconditions. However, the performance

of natural enemies is highly dependent on the croppingsystems, especially the diversity of

various host plants of H. armigera. For example, thenatural parasitism of H. armigera by a

larval parasitoid, Campoletis chlorideae, was significantlyhigher on a wild plant, Solanum

viarum than on tomato (Srinivasan, 2003). Since H. armigerafemale moths overwhelmingly

oviposit on S. viarum (Srinivasan et al., 2006) and thusthe larvae also voraciously feed on

this plant species than tomato (Srinivasan et al., 2005),C. chlorideae might have preferred

to attack H. armigera on S. viarum than on tomato. Thus,the efforts on biological control

of H. armigera in tomato production systems could bediluted by the presence of other

most preferred host plants in the same environment.

8 Armyworms

Among the Spodoptera spp., Spodoptera litura is thepredominant pest on tomato. Like

H. armigera, S. litura is also a polyphagous and highlymobile insect which feeds on many

Figure 12 Helicoverpa armigera feeding damage on tomatofruits.

agricultural and horticultural crops as well as wildplants. Almost 120 plant species have

been recorded as its host plants (Noma et al., 2010). As anocturnal insect, the larvae feed

actively during night hours, but hide in the soil or plantdebris during the day. It is widely

present in Asia and Oceania, with limited distribution inparts of Europe and Africa. At

times, it may be confused with S. littoralis, which isusually found in the Mediterranean,

Middle East and Africa, because of very similar size andcolouration of the adults. Besides

S. litura (Fig. 13), S. exigua (Fig. 14) can sometimes poseserious threats to tomato

production in Southeast Asia.

The neonate larvae feed in group on leaf surfaces (Fig. 15)and thus causing rapid

skeletonization leaving a papery structure. The grown-uplarvae feed on the whole leaves

and only main veins are left. Rarely, it can also feed onthe immature stages of tomato

fruits. However, S. litura does not bore like H. armigeraon the fruits. Sometimes, the larvae

may also cut the seedlings or young plants at soil level.

Figure 13 Larva of Spodoptera litura.

Figure 14 Larva of Spodoptera exigua.

S. litura adult is a stout-bodied and brown coloured moth.The forewings have numerous

criss-cross streaks in a cream or brown background. Thehind wings are white with a brown

patch along the border. A recent study confirmed that S.litura is a protogynous species,

in which female moths emerge earlier than male moths toavoid the risk of inbreeding in

natural conditions (Li et al., 2014). S. litura alsoproduces a multi-component sex pheromone

and it contains (Z,E)-9,11-tetradecadienyl acetate as amajor compound and (Z,E)-9,12

tetradecadienyl acetate as a minor compound (Tamaki et al.,1973). However, two additional

minor compounds, viz., (Z)-9-tetradecenyl acetate and(E)-11-tetradecenyl acetate have

been identified from the Chinese S. litura population (Sunet al., 2002). The eggs are laid

in groups of 100–300, and covered with the brown hairs fromthe body of the mother. The

translucent green neonate larvae remain gregarious andfeed. The grown-up larvae are

green, brown or black in colour, stout, cylindrical bodywith prominent black spiracles. The

body may have transverse and longitudinal grey and yellowbands. The larva passes through

six instars. The shiny reddish-brown pupae are found insoil. The total developmental time is

about five weeks, and it is usually one day or a few daysshorter for female adults.

Temperature is an important abiotic factor that influences

the development and damage

potential of S. litura. A recent study involving S. lituraon peanut concluded that increase

in temperature could increase the number of generations,reduce the generation time

and thus resulting in higher incidences of S. litura(Srinivasa Rao et al., 2015). Besides

temperature, continuous rise in the atmospheric CO 2concentration could also favour

S. litura. For instance, at elevated CO 2 , nitrogencontent decreased in mung bean whereas

the levels of non-structural carbohydrates increased,resulting in increased consumption

by S. litura (Srivastava et al., 2002). Thus, warm weatherseems to favour the expansion

and damage potential of S. litura.

A large number of natural enemies including parasitoids,predators, pathogens and

nematodes are reported to kill S. litura. Larval stage ishighly prone to parasitism, and

about 58 larval parasitoids, mostly braconids have beenreported (CABI, 2015). However,

as in the case of H. armigera, the parasitism of S. liturais highly dependent on the presence

of associated host plants in a particular ecosystem. Forinstance, higher rates of S. litura

parasitism by Microplitis prodeniae and C. chlorideae arecommon with taro as a trap crop

(Zhou et al., 2010). Among the pathogens, protozoa, fungi,viruses including granulovirus

and nematodes are important natural mortality factors.

Figure 15 Feeding damage of neonate larvae of Spodopteralitura.

9 Spider mites

Spider mites emerged as serious pests of vegetable crops inSouth- and Southeast

Asia, Africa, Europe and Mediterranean countries. They arepolyphagous. For example,

Tetranychus urticae was widely reported to feed on morethan 140 different plant families

and 1100 plant species including tomato. T. urticae iscommonly known as two-spotted

spider mite and T. cinnabarinus as carmine spider mite,while T. evansi as red spider mite.

T. evansi (Fig. 16) is the predominant species in severalcountries in Africa on tomato and

other solanaceous vegetables.

Spider mites usually extract the cell contents from theleaves using their long stylet.

This results in reduced chlorophyll content in the leaves,leading to the formation of

several white or yellow speckles on the leaves (Fig. 17).In severe infestations, leaves will

completely desiccate and drop off. In addition, spidermites can also feed directly on

immature fruits resulting in economic losses. The mitesalso produce webbing on the leaf

Figure 16 Red spider mite infestation on tomato.

Figure 17 Feeding damage of red spider mite.

surfaces, and in severe conditions, the whole plant isconfined with the webs (Fig. 18) and

thus resulting in complete crop failure.

T. urticae is minute in size and green, greenish yellow,brown or red in colour with two

dark spots on the body. Whitish eggs are round, and uponhatching, it passes through a

larval stage and two nymphal stages before becoming adult.The life cycle is completed

in one to two weeks and hence there are several overlappinggenerations in a year.

T. cinnabarinus is similar to two-spotted spider mite, butcarmine in colour. T. evansi is also

similar to two-spotted spider mite.

Warm, dry conditions with the low relative humidity favourrapid build-up of spider

mite population and result in increased feeding.Precipitation is the only important abiotic

factor that restricts spider mite population. A CLIMEXmodel predicted that Mediterranean

region has the potential to be extensively colonized by T.evansi on tomato because of its

relatively mild winter and wide expansion of the mite tonew areas in Africa is also predicted

(Migeon et al., 2009). In addition, they confirmed that itspotential distribution seemingly

limited by cold stress in North America and Eurasia.Several predators of spider mites such

as Stethorus spp., Oligota spp., Anthrocnodax occidentalis,Feltiella minuta, lacewing

(Mallada basalis and Chrysoperla carnea) and predatorymites (Phytoseiulus persimilis,

Amblyseius womersleyi and A. fallacis) occur in most of thecountries. However, they may

not provide significant control of spider mites especiallyin open field conditions, because

of their high reproductive ability and rapid development.Under long-night photoperiod

and low temperature, T. urticae mostly undergoes diapausein some regions. Interestingly,

the percentage diapause induction increases in spider mitepopulations under predation

risk (Kroon et al., 2004). Although a couple of pathogenicorganisms have been reported

to infect spider mites, a fungal pathogen, Neozygitesfloridana is an important cause of

mortality in T. evansi population in Brazil and East Africa(Wekesa et al., 2007). Thus, spider

mite population is also partly regulated by the naturalenemies.

10 Conclusions

Tomato is infested by a range of insect and mite pestsstarting from the seedling stage

until the final harvest. Early season sucking insectsmostly cause foliar damages. However,

Figure 18 Webbing caused by red spider mite.

the onset of whitefly early in the season can lead tocomplete crop loss because of its

vectoral abilities to transmit begomoviruses on tomato.Fruit borers are a serious problem

during the reproductive phase of the crop. The recentinvasive South American leaf

miner appears to pose a considerable threat to the tomatoindustry in the tropics. Mostly,

warming weather conditions favour the tomato pestspositively, although occasional

advantages for the natural enemies have also been reported.There are several natural

enemies and disease causing pathogens documented againstthese pests in different

parts of the world. However, the potential of these natural

enemies is limited by various

factors including changing landscapes as well as climate,extensive reliance on chemical

pesticides and so on. However, it is possible to exploitspecies-specific natural enemies

and entomopathogens, and integrate them with othercompatible components such as

resistant cultivars and pheromones. Hence, a thoroughknowledge and understanding of

the changing pest profiles and their bio-ecology in tomatoproduction systems is highly

imperative to develop and deploy such an effectiveintegrated pest management strategy

in the tropics.


Further information on the life-cycle and pest managementoptions for various insect

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17 Chapter 17 Developingdisease-resistant tomato varieties

1 Introduction

Tomato (Solanum lycopersicum L.) is the second mostimportant vegetable crop after

potato in the world (FAOSTAT, 2014). In addition to beingconsumed as a fresh vegetable,

it is also used as a salad, in ketchup, as a puree, as apickle and in many other forms,

depending on the growing region of the world. In 2013, itwas estimated that 4.7 million

ha of tomatoes were grown worldwide, producing more than164 million mt of fruit

(FAOSTAT, 2014). China has consistently been the largestproducer of tomatoes for many

years, with the United States second, although India hassurpassed the United States

in production since 2011. In the United States, tomatoesare grown in an area of about

175 000 ha producing about 11.5 million mt annually(USDA-NASS, 2013). In addition

to being an important vegetable crop worldwide, tomato isalso used as a model plant

species for genetic studies related to fruit quality,stress tolerance (biotic and abiotic), and

other physiological traits. It is widely adapted to manyclimates around the world spanning

tropical to temperate regions. In order to meet the demandfor tomatoes, it is also grown

in greenhouses. Because of its economic contribution to theagriculture industry, there is

abundant interest in using genomic tools to improve tomatoand develop new varieties

(Panthee and Chen, 2010; Paran and van der Knaap, 2007).

As a global species, tomato is known to be afflicted by atleast 200 different disease

causing organisms from most major pathogen classes –bacteria, fungi (including

Oomycota), viruses and nematodes. Despite decades ofconventional breeding and

selection, there are still a large number of diseasescaused by these pathogen classes that

make tomato production challenging in various parts of theworld (Agrios, 2005). Current

advances in tomato genetics and genomics can be combinedwith conventional plant

breeding methods to introgress the gene of interest andexpedite the breeding process.

In this chapter, we summarize the historical aspect oftomato variety development and

the current status of the application of technology towardsthe development of disease

resistant varieties.

Disease resistance breeding has been a valuable andfundamental part of modern

tomato improvement efforts, with roots in the 1930s (Scott,2005c). An overarching theme

may be observed for disease resistance breeding in tomato.Historically, the field has

enjoyed many discoveries of qualitative monogenic dominantresistances effective against

many major global pathogens, especially soil-borne fungalpathogens. These resistance

genes continue to provide effective disease controlglobally, and are widely deployed

in modern tomato varieties because of it (Scott, 2005c).

Examples include the disease

resistant loci I (immunity to Fusarium wilt), Mi(Meloidogyne spp.), Sw (tomato spotted wilt

virus), Tm-2 2 (tomato mosaic virus), Sm (Stemphyliumspp.) and Ve (Verticillium), among

others, which are regular components of modern cultivardevelopment programmes

(Scott, 2007; Scott and Gardner, 2007). Despite beingbroadly used for many years,

relatively few pathogen strains have been selected thatovercome these classic genes

(Scott, 2005c). In stark contrast are the bacterial andfoliar fungal diseases of tomato, such

as Phytophthora infestans, Alternaria spp., Septoria spp.,Xanthomonas spp. and Ralstonia

solanacearum, which continue to severely thwart geneticmanagement efforts. New strains

of P. infestans have overcome deployed resistance genes;new species of Xanthomonas

have been found when resistance genes to the presentspecies have been deployed;

and resistance to Alternaria, Septoria and R. solanacearumhave been difficult to identify

and introgress from wild Solanum species into cultivatedtomato. Genetic improvement

for resistance to these pathogens has been arduous,requiring introgression from wild

relatives and unimproved tomato lines (Scott, 2005c). Anexception is the immune type of

resistance to bacterial speck (BSP; Pseudomonas syringaepv. tomato), which is governed

by the Pto gene, although the gene has not remained asdurable as others such as Mi

(Martin et al., 1993a; Scott, 2005c). Breeding for virusresistance has been of a more

blended nature, with cases of good resistance occurringwith one or a few genes, and

gene pyramiding has shown great promise for obtaining highlevels of resistance, but with

greater risk of selection for virulent viral variants(Hanson et al., 2016; Scott, 2005a).

The discussion of disease resistance breeding shouldclarify our current understanding

of host–pathogen interactions genetically, biochemically,spatially and temporally, as

well as the use of race-specific resistance forclassification. Historically, breeders have

tended not to prefer breeding for partial resistance (oftenconsidered to be tolerance)

because it is difficult to quantify and to obtain highlevels of resistance, and because

single-gene immunity (typically associated with ahypersensitive response) has historically

been considered the ideal resistance type (Ellis et al.,2014; Mundt, 2014). On the other

hand, for some important tomato pathosystems, particularlythe bacterial and foliar fungal

diseases, partial, quantitative resistance is the only typethat has been documented so far.

Quantitative resistance, however, tends to provide greaterresistance durability over time,

space and pathogenic strain variation in many crops andpathosystems, and can improve

the durability of monogenic immunity types of resistancegenes (Ellis et al., 2014; Palloix

et al., 2009; Parlevliet, 2002; Quenouille et al., 2013,2014). Durability is also affected

by the genetic diversity and reproduction strategies ofpathogens, highlighting the

importance of linking pathogen biology and diversity withresistance breeding strategies

(McDonald and Linde, 2002). Our review documents theprogress that has been made in

the field of tomato resistance breeding, but the challengefuture plant breeders face is

how to effectively and intelligently identify, deploy andsafeguard the precious resource of

tomato resistance genetics.

2 Bacterial disease resistance breeding

Tomato in the United States is afflicted primarily by fivebacterial diseases (four foliar/

canopy and one soil-borne), which are noteworthy due totheir broad distribution and

impact on tomato production around the world. These arebacterial canker (BC) (Clavibacter

michiganensis pv. michiganensis; Cmm), BSP (Pseudomonassyringae pv. tomato; Pst),

bacterial spot (BSX) (Xanthomonas spp.), bacterial wilt(BW) (Ralstonia solanacearum;

Rs) and pith necrosis/bacterial stem rot (PN) (Pseudomonasspp. and Pectobacterium

carotovorum subsp. carotovorum; Pcc) (Agrios, 2005). Notmuch breeding work has been

done for Pcc as it is less of an economic concern than theothers, so we will not devote

any more time to it. Interested researchers may findadditional information here (Catara,

2007; Molan and Ibrahim, 2007; Moura et al., 2005; Powellet al., 2013), including a report

on possible genetic resistance in tomato (Ustun et al.,2009). A survey of the contributing

community of the peer-reviewed journal Molecular PlantPathology (458 votes) considered

what were the Top 10 plant pathogenic bacteria based uponscientific interest and

economic importance (Mansfield et al., 2012). The resultsincluded three of the tomato

bacterial pathogens – Pst pathovars, Rs and Pcc ranked 1, 2and 10, respectively, with

several other species of Xanthomonas making the list aswell (4th–6th). Cmm received an

honourable mention. Although tomato is not the only cropthese pathogens afflict, the

survey highlights the global importance of the tomatobacterial pathogens economically

and scientifically. It follows, then, that research anddevelopment into the plant–pathogen

interactions, genetics and management of tomato bacterialpathogens may play a

fundamental role in improving management of those diseasesin other crops as well, with

tomato research leading the way.

The tomato bacterial pathosystems share some commonfeatures. These pathogens

cause damage by infecting plant vegetative tissues (leaves,stems and roots) leading to

localized tissue death and decay, which may result in arapid or drawn out plant death,

leading to substantial yield loss (Agrios, 2005). Fruitlesions may also develop for the foliar

diseases, leading to direct losses of marketable fruit.Although the site of entry varies

between each pathogen, damage is concentrated to theabove-ground organs and tissue

systems; root damage is not a major factor for thesebacterial diseases (Agrios, 2005).

Even for the soil-borne R. solanacearum, root damage is nota major factor in disease

development, but rather bacterial activity in the lowerstem following migration through

the roots (Schell, 2000). Insect vectors are not thought tobe significantly involved as

vectors in any of the major bacterial diseases (Agrios,2005). Water is the primary dispersal

mechanism for pathogen spread from plant to plant,particularly windblown rain. Sites of

infection include open wounds (pruning and stringing) andnatural openings (stomata,

hydathodes and sites of lateral root formation).Long-distance dispersal is facilitated by

contaminated seeds and soil (Agrios, 2005). While Pst andthe Xanthomonads can be

spread on the surface of seeds, Cmm is unique in that itcan infect the seeds internally,

leading to strong concerns about rapid spread to manytomato growing regions in a given

season (Francis et al., 2001) The Xanthomonads can survivein unfavourable conditions

and as an epiphyte in latently infected host leaf tissuesand weeds (Stall et al., 2009a). Rs

is typically spread by infested soil and flowing water(floods, rainwash and irrigation), while

Pcc is spread by rainsplash onto open stem wounds (Agrios,2005). Rs can also be found

in the virgin soils of the southeastern United States thathave been cleared for farmland

(Kelman, 1953). Density-dependent quorum sensing is acommon feature of bacterial

pathogenesis, such that transition from one phase of thedisease cycle to the next often

requires a latent period where the pathogen densityincreases to a threshold level. This

phenomenon has received a lot of study in the BWpathosystem (Schell, 2000).

Another feature the bacterial diseases of tomato have incommon is that they are very

difficult to manage, with somewhat of an exception for BSP.Chemical control methods

are generally moderately to poorly effective for thebacterial pathogens in many crops,

and tomato is no exception. Copper-based pesticides are theprimary control methods

in the field while the antibiotic streptomycin may be usedto treat seedlings; however,

copper- and streptomycin-resistant strains are reported inthe pathogen populations

(Ritchie and Dittapongpitch, 1991; Stall et al., 2009a).The broad use of antibiotics has

been tightly regulated in agriculture, due to concerns ofnegative impacts on human

disease management, greatly restricting when they may beapplied (Kemble et al., 2016).

Sanitation practices can help reduce the severity of somebacterial diseases, removing

plant debris and weeds that harbour pathogen populations(Agrios, 2005).

Use of genetic resistance is greatly desired as part of aneffective integrated pest

management strategy for the bacterial pathogens of tomato.

Breeding for resistance,

however, has historically been very difficult, without manygains occurring even after

several decades as demonstrated by the lack of resistantvarieties on the market (Scott,

2005; Stall et al., 2009). There are several componentsthat have contributed to the overall

lack of progress.

First, deployment of host resistance genetics has led to aninadvertent selection for

pathogen variants that overcome those genes (Mundt, 2014;Scott, 2005). After the

widespread deployment of a new resistance gene, new racesor species of the pathogen

capable of overcoming the resistance genes have emerged.This is particularly evident

in the development of BSX resistance in the southeasternUnited States where years of

resistance breeding have failed to generate durableresistance due to complex changes in

the race and species structures of the pathogen (Scott etal., 2015b).

Second, durable resistance to the bacterial pathogensconferred by immune-type genes

is lacking in tomato (Scott, 2005c; Sen et al., 2015a;Stall et al., 2009a; Thapa et al., 2015b).

Field resistance to the bacterial pathogens is generallyquantitative, partial and polygenic

in nature, being determined by multiple quantitative traitloci (QTL), each contributing

a portion of resistance. Pst resistance is somewhat of anexception because the Pto

gene provides a strong, immune-type reaction to race T0 of

the pathogen, exhibiting a

hypersensitive response, although race T1 has emerged thatovercomes Pto (Yang and

Francis, 2007a). Although genes that induce ahypersensitive response have been reported

against the Xanthomonad race/species structure, they do notall necessarily correlate

with field resistance, and those that do correlate havebeen overcome (Stall et al., 2009).

Breeding multiple loci into a single adapted variety hasbeen a very difficult task, although

the development of molecular markers for marker-assistedselection (MAS) has generated

some useful breeding materials for tomato bacterialdiseases (Yang and Francis, 2007a).

Third, most of the bacterial resistance traits have beenintrogressed from wild relatives

of tomato, including S. pimpinellifolium, S. lycopersicumvar. cerasiformae, S. peruvianum,

S. habrochaites, S. parviflorum, S. chilense and unimprovedS. lycopersicum. The trait

introgression process from these wild relatives inherentlybrings along many undesirable

traits through linkage drag, requiring many generations ofbackcrossing with commercially

viable lines to purify the material of those undesirabletraits, all the while selecting for

resistance (Francis et al., 2001; Scott, 2005a; Scott etal., 2005a; Sen et al., 2015a; Stall

et al., 2009a). A classic example is the tight associationbetween BW resistance and fruit

size. Many decades of breeding have failed to uncouplethese linkages, such that a step

towards higher resistance is usually associated withsmaller fruit size (Acosta, 1978; Acosta

et al., 1964; Scott, 2005b). An exception is discussed inthe BW section below. Despite

these challenges, significant progress has been made insome cases and are discussed for

specific bacterial pathosystems, highlighting successfulmethodologies and the unique

challenges of each specific disease.

2.1 Bacterial canker

An excellent review on the various aspects of BC and tomatoresistance is available

(Sen et al., 2015b). Originally described in Michigan, in1910, BC has plagued tomato

production and resistance breeding ever since. Cmm is axylem-invading organism mostly

of solanaceous crops, and is the only Gram-positive tomatobacterial pathogen. As

mentioned previously, Cmm can infect tomato seedsinternally (Tancos et al., 2013), which

is a major factor for why many researchers consider it tobe the most important tomato

bacterial disease, along with its potential to causesubstantial yield losses (Sen et al.,

2015b). Cmm is a quarantine pathogen in the European Unionand many other countries

(de León et al., 2008), which has substantial effects ontomato export/import dynamics,

particularly with regard to seed sales.

Cmm has been classified into four genetic subgroups (A–D)and may be a species complex

(Francis et al., 2001; Louws et al., 1998). Breedersworking on Cmm resistance should keep

these groups in mind and look for lines that resist allfour groups. In an assessment of

tomato germplasm against Cmm strains A through C, Franciset al. (2011) did not observe

significant differences in disease by strain, suggestingthat the sources of resistance tested

would perform similarly across those three strains. Cmmpathogenicity genes are clustered

in unique regions of the genomes as ‘pathogenicityislands’, suggesting that they were

obtained from another source by horizontal gene transfer(Sen et al., 2015b).

Typical symptoms of the disease are stunting of youngplants; one-sided wilt to full

wilting; yellow-brown marginal leaf necrosis; internalvascular decay; and the typical canker

spots on leaves, petioles, stems and fruit, which have adark center with a white halo,

giving it the apparent ‘birds-eye’ appearance (de León etal., 2008; Sen et al., 2015b).

Plant death may eventually result due to wilting. Primarytransmission is from infected seed

or plant debris, while secondary infection occurs throughwounds and natural openings,

after which the pathogen penetrates the vasculature andbecomes systemic throughout

the plant. Mature plants may become infected, but tend toremain asymptomatic and yield

losses are not significant, indicating what has been termedthe ‘window of vulnerability’

between transplanting and the 18–19 leaf stage (Sharabaniet al., 2013).

The current view of Cmm pathogenesis is that the bacterium

colonizes the plant as an

endophyte, doing little harm to the plant and avoiding orsuppressing host defences. After

some time, the bacterial cell density increases and quorumsensing signals reach a critical

threshold (calculated as 10 8 CFU/g plant material),inducing a transition to pathogenic

behaviour, which matches the time when wilting begins tooccur in the plant (Sen et al.,

2015b). Upon infection, the bacteria penetrate into thexylem vessels, allowing for rapid

vertical and horizontal spread. Ethylene response genes areinduced in the plant by Cmm,

which has been suggested to be involved in enhancing hostsusceptibility (Balaji et al.,

2008). The bacteria penetrate the phloem tissues andsubsequently degrade them, but

the structural features of the sieve tubes do not allow forfree bacterial movement in the

phloem. No vessel plugging compounds have been implicatedas wilt inducing, so it is

thought that some kind of toxin may be involved (Sen etal., 2015b; Wallis, 1977). It is not

clear what mechanisms are employed by resistant plants tocombat infection nor what

portion of the disease cycle is inhibited. It is suggestedthat structural and developmental

differences in the xylem, particularly of the hypocotylregion, between S. lycopersicum

and its wild relative species may be the mechanism ofresistance, since they have a more

robust vessel structure, faster growth, a different shapeand a shorter time period for

the root–shoot transition to occur in seedlings. The QTLsfor these traits reside in the

same region as resistance QTLs (Sen et al., 2015b). Highplant resistance levels lead to an

increase in the latent incubation period of the Cmm (Changet al., 1992).

Genetic resistance is polygenic; quantitative, with atolerance type of action; and resistance

is not available in commercial varieties (Sen et al.,2015b). The well-known tomato lines

IRAT-L3 and ‘Hawaii 7998’, along with several wildaccessions have exhibited resistance

to BC. Resistance was identified as early as 1934 inaccessions of S. pimpinellifolium,

then later in S. habrochaites, S. lycopersicum and S.peruvianum, and more recently in

S. hirsutum and another S. peruvianum (Francis et al.,2001; Sen et al., 2013; van Heusden

et al., 1999a). Initial breeding efforts to ingressresistance into cultivated germplasm

resulted in the development of ‘Bulgaria 12’, ‘Heinz 2990’and ‘Okitsu sozai 1-20’, which

exhibited reduced wilting symptoms but retained a highbacterial titre. The main problem

with these lines, however, was that further efforts tohybridize them with other cultivated

varieties failed to transfer the resistance due tocomplexities of the genetic background

(Sen et al., 2013, 2015b).

Multiple researchers have investigated aspects of genenumber and expression patterns.

In germplasm that has been tested for Cmm resistance,resistance generally appears to be

conferred by one to eleven genes, up to four of which havemajor effects and others act as

small effect modifiers (Sen et al., 2015). Gene actions aresomewhat diverse, depending

upon the source, with reports of dominant, incompletelydominant, recessive and additive

types. Environmental variation and the nature of thegenetic background can influence the

apparent type of interactions between resistance genes,further complicating breeding

assessments. Heritability of resistance appears to bemoderate to high in cases where

it was calculated, although the authors cautioned againstconsidering heritability as the

breeding value of the resistance sources due to thedynamics of the experiments (Francis

et al., 2001).

Breeding methods have relied upon traditional backcrossingstrategies, although MAS

is greatly desired. One issue with introgressing resistancefrom the wild relatives into

cultivated tomato is that generating viable offspring canbe challenging. For example,

crosses between cultivated tomato and S. peruvianum haveviability issues that require

tissue culture techniques for embryo and ovule rescue inhybrids and backcross populations

(Sandbrink et al., 1995; van Heusden et al., 1999b).Complex inheritance with negative

traits for yield, size and taste also confound breedingefforts.

There are several aspects of Cmm resistance that remainunclear, and their elucidation

would directly benefit resistance breeding. These include(1) clarification of resistance

mechanisms, especially in distinguishing between what areinnate structural variations

and what are induced responses, and what aspects of thedisease pathway they affect

(seed infection, vascular colonization and systemicspread); (2) development of markers

for each unique source of resistance to facilitate MAS; and(3) comparative screening of

each unique resistance source with the four genetic groupsof Cmm to test for race-like

resistances and general durability.

2.2 Bacterial speck

Tomato production in cool, moist climates and seasons hashad to combat BSP, particularly

the processing tomato industry. BSP is a foliar disease oftomato characterized by very

small necrotic lesions, often with discrete yellow halosaround the margin of the lesion. In

recent years, BSP has exhibited somewhat of a resurgence asan economically important

pathogen (Kozik, 2002a; Kozik and Sobiczewski, 2000;Mansfield et al., 2012). BSP is

somewhat unique compared to the other bacterial pathogens,both in the level of research

effort about it, as well as due to some unique resistancefeatures.

Pst has become a well-established model system forbacterial pathogenesis, and has

had a tremendous impact on our understanding of pathogenbiology, pathogenesis

and host–parasite interactions. The scientific impact of

Pst includes major contributions

towards the characterization of the hypersensitive response(HypR) associated with a

plant immune reaction, which is induced by the Pst hrp genecluster that codes for the

type-III secretion system, as well as other majordiscoveries in effector trafficking to the

host plant and their suppression of host defences(Mansfield, 2012). Foundational work in

deciphering the differences between the basal defencesystem (PTI) and effector-induced

defence system (ETI), as well as many discoveries of thespecific components and value

of each system have been accomplished with Pst at the focus(Dodds and Rathjen, 2010;

Jones and Dangl, 2006; Postel and Kemmerling, 2009).

Infection of tomato tissues occurs through wounds andnatural openings, where plant

pattern-recognition receptors are concentrated fordetection of pathogen features (Beck

et al., 2014). Successful infection requires thesuppression of the host basal defence system

(Rosli et al., 2013; Zipfel and Robatzek, 2010), allowingfor Pst activity to cause small lesions.

The phytotoxin coronatine, a multifunctional toxin, is veryimportant for full virulence of

the pathogen, improving invasion through the stomata,bacterial multiplication in the leaf

apoplast and development of disease symptoms such as thechlorotic halo effect (Geng

et al., 2012). BSP symptoms can easily be confused with theearly stages of BSX, especially

on leaves, stems and petioles; however, fruit infections

are very diagnostic for discerning

between the two diseases. BSP symptoms on the fruit developas very tiny spots (1.5 mm

in diameter; truly a speck), are slightly raised and remainsuperficial, whereas BSX fruit spot

symptoms are larger, lead to cracking and often becomescaly. On the leaves, BSP and

BSX lesions may coalesce over time and lead to defoliation,although BSX spots do not

have the halo effect that BSP spots generally have. Initialinoculum comes from soil, plant

debris and infected seeds, making seed treatments importantfor disease management

(Agrios, 2005).

Resistance to BSP in tomatoes has classically revolvedaround the deployment of the

well-known Pto-1 (referred to as Pto) gene, which triggersa hypersensitive response upon

contact with Pst, successfully halting further invasion andsymptom development. Pto was

originally identified in S. pimpinellifolium and thenrapidly cloned and widely introgressed

into the cultivated tomato germplasm (Martin, 1994; Martinet al., 1993b,c). The Pto gene

generally has dominant action, or additive in some cases,and is one of four Pto genes

in tomato; however, it is the only one widely used for BSPresistance (Yang and Francis,

2007b). Strains of Pst expressing the AvrPto or AvrPtoBeffector genes trigger the Pto

mediated defence reaction, which are designated as race T0.Pto proved to be quite

effective for BSP resistance for about 20 years until the

emergence of race T1, which

overcomes Pto (Pedley and Martin, 2003; Pitblado and Kerr,1979; Pitblado and Kerr,

1980) via changes in the expression patterns and amino acidsequences of AvrPto and

AvrPtoB (Kunkeaw et al., 2010). The prevalent T1 strainsform a highly related, single

lineage, suggesting that it was the high selection pressureof the widely deployed Pto that

rapidly selected for variations in AvrPto and AvrPtoB. Thissuggests that new sources of

resistance will be effective against all the known T1strains (Thapa et al., 2015a).

With the emergence of Pst T1, breeders are once again facedwith the task of finding non

Pto-based resistance. Breeders have continued toincorporate Pto into new germplasm,

indicating that it still has effective value (Kozik, 2002b;Kozik and Nowakowska, 2010; Yang

and Francis, 2005; Zaccardelli et al., 2011). Otherbreeders have gone back to the wild

relative germplasm pools in an effort to identify novelresistance against T1. Quantitative

resistance has been identified in several lines of S.habrochaites, S. peruvianum and one

S. chilense (Thapa et al., 2015a). The researchers mappedthe resistance QTLs using a set

of introgression lines from the most resistant S.habrochaites line LA 1777, identifying four

QTLs on three chromosomes. Another S. habrochaites line LA2109 was recently reported

to carry resistance to some strains of race 1 but not all,along with other accessions from

the same geographic region (Bao et al., 2015). The authorsdetermined that a mixture of

Pto-dependent and -independent resistance mechanisms werepresent in the line, and

genetic mapping efforts identified two QTLs on chromosomes2 and 8 that were related

to resistance. A set of candidate genes were proposed forthe chromosome 2 loci. Some

Bulgarian tomato lines may be another source for resistanceto race T1 (Aleksandrova et

al., 2013).

Currently, there are several summary points that seempertinent for the future of BSP

breeding: (1) Breeders continue to introgress Pto as avaluable component of disease

management efforts around the world, despite the presenceof race T1. (2) Resistance

sources for T1 have been identified in wild relatives ofcultivated tomato, and may be a

mixture of quantitative and immunity-type resistances,which means breeders working to

introgress them into cultivated varieties should be able togain a lot of helpful guidance

on what has worked for the other tomato bacterial diseasesystems, hopefully improving

efficiency, success rates and combining loci to enhancedurability before wide deployment

of resistance. And, (3) breeding efforts for resistance toBSP may be improved by assessing

the population diversity of Pst around the world, as hasbeen worked on in the other major

tomato bacterial pathosystems (Lebeau et al., 2011; Prioret al., 2016; Sen et al., 2015;

Stall et al., 2009). By definition, T1 is everything thatis not T0. Thus, a detailed assessment

of population diversity phylogenetically and effector-basedfrom around the world would

be helpful in interpreting reports on resistance, as wellas aiding breeders in selecting

for resistances that hold up to regional or localized T1strains. A few reports along these

lines are available, indicating frequent pathogen movementbetween North America and

Europe, low genetic diversity and the presence of strongselection pressure for altered

expression and gene sequences of avrPto and avrPtoB (Cai etal., 2011; Campanile and

Zaccardelli, 2011; Kunkeaw et al., 2010; Vinatzer et al.,2015).

2.3 Bacterial spot

Bacterial spot (BSX) is a foliar disease caused by severalspecies of Xanthomonas. As a

genus, the xanthomonads are major bacterial pathogens ofmany important crops besides

tomato, including rice, cassava, citrus, cruciferous andsolanaceous crops (Mansfield et al.,

2012). Classification of the causal species of BSX intomato has a somewhat confusing

history, especially with the relationship between race andspecies. What were originally

considered to be new races of the pathogen often turned outto be different species

of Xanthomonas altogether (collectively referred to asXanthomonas spp.). Races are

designated with a ‘T’. As it currently stands, BSX oftomato is caused by X. euvesicatoria

(T1; Xe), X. vesicatoria (T2; Xv), X. perforens (T3–T5; Xp)and X. gardneri (no race

designations have been described so far; Xg) (Jones et al.,2004; Scott et al., 2015b). T5

has not yet been confirmed. It is obvious that a geneticdetermination of species does not

correlate well with the host–parasite gene interactionsthat led to the race designations.

This indicates that breeding efforts for BSX resistanceneed to take both race and species

information into account when assessing germplasm;greenhouse studies should not rely

upon a single race or species, while field resistancescreens should identify the specific

species and races presently causing disease during eachfield season. It also indicates that

apparent breakdowns in tomato resistance may not always bedue to changes in gene

effectiveness, but rather due to shifts in the frequenciesof each species in the environment.

The mechanisms of Xanthomonas spp. pathogenesis andtransmission are similar to

Pst, as described previously. Symptomatically, BSX ischaracterized by larger, non-haloing

grey-black spots on all foliar organs, with leaves beingthe most affected (Stall et al., 2009).

The undersides of the lesions are often described as havinga ‘greasy’ appearance, and

the centre of the spot may fall out as in the case of Xpinfection, forming ‘shot holes’.

The disease is spread by free water, particularly byrainsplash in heavy rainstorms (Agrios,

2005). Xanthomonas spp. can also infect the exterior of theseed, allowing for transference

over long distances and into new growing regions.Xanthomonas spp. generally cause a

more aggressive disease than Pst, and may be outcompetingPst in the Southeast US.

Infected transplant seedlings can lead to rapid spread ofBSX in greenhouses, and any

flats with infected plants should be discarded, asneighbouring plants can be latently

infected over time. The pathogen can overwinter on plantresidues, making sanitation

efforts an important part of an IPM strategy (Stall et al.,2009), although in many parts of

the southeastern US, there is sufficient inoculum in thesurrounding environment to cause

strong epidemics each year. In contrast to BSP, BSX needs awarmer humid environment

to develop.

Like the other bacterial pathogens, resistance to BSX isboth polygenic and quantitative,

with single QTLs conferring partial resistance (Scott,2005b). Dr. Jay Scott’s breeding

programme at the University of Florida has been a leaderfor over 30 years in breeding

tomatoes for resistance to BSX, yet there remains novariety on the market with high

levels of BSX resistance across the multiple species andraces, highlighting the difficulties

associated with BSX (Scott et al., 2015b). Each time aresistance source was identified for

a particular race, a new race would be selected that couldovercome the resistance, even

before the line was ready to be released. The currentbreeding strategy is to go back to

the wild germplasm pools and screen for broad-spectrumresistance, which shows promise

so far with the discovery of BSX resistance in PI 114490, ayellow cherry-type tomato

collected from the Royal Botanical Gardens in Kew, England(Scott et al., 2003, 2006a).

Multiple resistance genes/loci for BSX have been identifiedin tomato and recently

summarized (Pei et al., 2012). ‘Hawaii 7998’ is adifferential line for identifying race T1, which

are Xanthomonas spp. carrying the AvrRxv gene, and isassociated with a HypR (Whalen

et al., 1993). ‘Hawaii 7998’ remains the most reliablesource of resistance to T1 (Jones and

Scott, 1986; Pei et al., 2012), which is conferred by threeindependent loci (rx1 and rx2

on opposite arms of chromosome 1 and rx3 on chromosome 5)and may be modified by

three susceptibility loci on chromosomes 3, 9 and 11 (Yu etal., 1995). The dominant allele

Rx3 confers quantitative resistance in the field,explaining 41% of the phenotypic variation

(Yang and Francis, 2005) and is considered to be the mosteffective loci for T1 resistance.

It is not clear yet whether rx3 and Rx3 are alleles of thesame gene, or closely associated

genes on the same chromosome (Pei et al., 2012). MAS hasbeen used to successfully

move Rx3 into coupling-phase linkage with Pto (Yang andFrancis, 2005).

Resistance to race T2 has been documented, including‘Hawaii 7983’ that expressed

partial resistance over multiple seasons, as well as

partial resistance to T1 (Scott et al.,

1997). PI 114490 was also reported to provide additivequantitative resistance via two

genes, and high levels of resistance required the presenceof all four alleles in the breeding

line (Scott et al., 2003).

As Xp contains the majority of the races (T3–T5), whichcause many annual epidemics in

tomato growing regions (Pereira et al., 2011; Scott et al.,2015b), much work has been done

to identify and breed resistance against this group of thexanthomonads. T3 resistance

has been identified in several lines (‘Hawaii 7981’, alongwith the S. pimpinellifolium

accessions PI 126932 and PI 128216), each conferring a HypRin the presence of the

pathogenic expression of the avrXv3 gene, and partialresistance in field assessments

(Scott et al., 1995). For these lines, quantitativeresistance is conferred by the single,

incompletely dominant gene Xv3) (Scott et al., 2001), whichwas mapped to the same

location and renamed as Rx4 in PI 128216 (Robbins et al.,2009). Xv3 and Rx4 may be the

same gene, are allelic, or are very tightly linked in thesame region (Wang et al., 2011).

‘Hawaii 7981’ contains some modifiers for Xv3/Rx4 (Scott etal., 2001), although none

were reported for PI 128216 (Robbins et al., 2009). Rx4 wasrecently cloned and a gene

based marker developed (Pei et al., 2012). The candidategene was identified as an NBS

LRR (nucleotide-binding sequence–leucine-rich repeat) class

of resistance gene, which

are typically associated with qualitative resistance andhypersensitive responses (Boller

and Felix, 2009). An association between the I-3 gene forFusarium wilt resistance and

susceptibility to T3 has been reported (Hutton et al.,2014).

T4 resistance has been identified in LA 716 (S. pennellii),being conferred by Xv4. The

physical location of the gene was reported on chromosome 3(Astua-Monge et al., 2000),

but was not successfully verified (Stall et al., 2009b).The previously mentioned PI 114490

also harbours strong resistance to T4, and will bediscussed more thoroughly below.

The tomato gene Bs4 (Ballvora et al., 2001) leads to HypRin the presence of avrBs4

and both are broadly dispersed in S. lycopersicum andXanthomonas spp. germplasm,

respectively, but Bs4 only confers resistance toXanthomonas spp. strains that cause

disease on pepper (Capsicum annuum) (Stall et al., 2009b).

PI 114490 is a unique resistant line in the BSX resistancebreeding realm. It was found to

be the most consistent source of strong resistance to T1,T2, T4 and X. gardneri, as well as

slightly less resistant to T3 (Scott et al., 1995, 1997,2003, 2006a, 2015b). Full resistance

has been difficult to recover during introgression, likelydue to losses of several QTLs

during the breeding process. Recent work to recover theresistance QTLs with greater

effectiveness involved a large series of multiple line

generation and divergent selections

under BSX pressure from the F2 to the F5 in Florida (Scottet al., 2015b). The advanced

generations were then tested in Ohio under strong BSXpressure, generating a strong

phenotypic dataset for QTL mapping. The genetic mappingefforts preliminarily identified

seven QTLs with strong effects on BSX resistance on fourchromosomes, five of which were

found to be broadly effective across races. Five additionalQTLs were found to have weak

effects on BSX resistance, with two being broadly effectiveacross races. The reduced

resistance on T3 might be complemented by crosses with aT3-resistant line, as described

previously.

A final important discovery for BSX resistance breeding isthe pepper gene Bs2,

which confers resistance to BSX in pepper, but is not knownto be present in the tomato

germplasm. Transgenic expression of Bs2 in tomato was shownto effectively confer

resistance to Xanthomonas spp. carrying the avrBs2 gene viathe induction of HypR

(Tai et al., 1999b). Field and greenhouse assessments oftomatoes carrying the Bs2

transgene showed strong resistance to T4, as well asproviding as much as a two-fold yield

boost compared to the non-transformed near isogenic lineswithout addition of copper

based bactericides (Scott et al., 2011, 2015b). Bs2 hasbeen introgressed into multiple

elite breeding lines in the University of Florida

programme, pyramiding with various other

disease resistances, although no cultivars have beenreleased yet due to regulatory and

consumer acceptance hurdles.

In summary, (1) multiple BSX resistance loci have beenidentified that generally confer

race-specific resistance, hypersensitive responses andprovide moderate to high levels

of quantitative control. None of those genes, however,confer broad-spectrum control,

compromising their deployment due to a lack of durability.Quantitative resistance loci are

generally considered more durable, especially whenpyramiding. It remains to be seen if the

nature of the broad-spectrum resistance in PI 114490 issimply a natural gene pyramiding,

or a novel form of resistance. (2) What are the populationdynamics in wild populations

of tomato-infecting Xanthomonas spp. with respect tospecies and race characteristics,

particularly over time? Do they interact in antagonistic,neutral or synergistic ways? For

example, Xp T3 was reported as an antagonist of Xe T1, andhas largely displaced it in

the southeastern US (Jones et al., 1998a,b). Theinteractions between T3–T5 and Xg has

not yet been characterized. Further evaluations may providethe biological context for

deployment of resistance, gene pyramiding and the overallexpected durability of the

resistant breeding material. And, (3) BSX resistancegenetics demonstrate how important

it is for breeders working on bacterial disease resistance

to regularly test the germplasm in

the field environment, rather than relying on a lab-basedinfiltration test, as a HypR does

not necessarily indicated qualitative resistance in thefield.

2.4 Bacterial wilt

BW is a soil-borne vascular wilt disease caused byRalstonia solanacearum (Rs), which

ranked as the second most important plant pathogenicbacterium economically and

scientifically (Mansfield et al., 2012). Rs prefers warm;wet; tropical to temperate regions

such as the southeastern United States, Central and SouthAmerica, South and East Asia

parts of Africa; and the Mediterranean nations. Rs has aglobal disease impact due to its

wide geographic distribution and a wide host range, causingdisease in over 250 species

in over 50 different plant families (Buddenhagen andKelman, 1964; Hayward, 1964, 1991,

1994, 1995; Kelman, 1953; Moorman, 2014; Olson, 2005).Notable groups include many

species in Solanaceae, banana (Musa spp.), Eucalyptus spp.,geranium (Pelargonium

spp.), cassava (Manihot esculenta), peanut (Arachishypogaea), many common weeds,

Zingiberaceae and Arabidopsis spp., although Arabidopsis isnot considered to be a

natural host.

BW of tomato is characterized by a rapid wilt that beginsin the newest leaves and leads

to whole plant collapse (Fig. 1), bacterial ooze from thevasculature and brown vascular

discolouration. Of the bacterial diseases of tomato, Rs isthe only truly soil-borne pathogen.

It infects through natural openings in the roots or throughwounds, where it then colonizes

the vasculature of the basal stem, continuing to spreadvertically and horizontally through

the vascular tissues until plant death (Hayward, 1991;Schell, 2000). Wilt occurs due to

disruption of water flow through the infected vasculature.The combination of Rs-produced

Figure 1 Bacterial wilt screening trial under heavyinoculum pressure of Ralstonia solanasearum in

North Carolina. In the picture, while some of the lines arewilting severely some of them are holding

up quite well showing a good level of variation inselection.

exopolysaccharide slime, high numbers of bacteria in thevessels, and Rs lytic activity leads

to the eventual wilt and death of the plant, while toxinsand tyloses are not thought to

have much effect on wilt (Hayward, 1991; Husain and Kelman,1958a,b; Nakaho and Allen,

2009; Nakaho et al., 2004). Genetic resistance is the onlyviable management strategy at

this time, due to the lack of season-long effectivechemistries (chloropicrin is the best) and

the long survival rate of Rs in the soil. Most of thestandard IPM strategies have helped

mitigate the spread of Rs, but provide little promise onceRs becomes established. Rs

is spread by water flow and contaminated seedlings or soil.It is not known to be able

to naturally infect the seed (Agrios, 2005; Chellemi et

al., 1994; Enfinger et al., 1979;

Kelman, 1953; Swanson et al., 2005; Vaughan, 1944).Effective field control has been

documented using resistant germplasm as rootstocks in agrafted vegetable production

system (Freeman et al., 2011; King et al., 2008; Louws etal., 2010; McAvoy et al., 2012;

Mian et al., 1995; Rivard and Louws, 2008; Rivard et al.,2012).

Formerly grouped in the Pseudomonas genus, Rs is nowconsidered to be a species

complex, containing multiple races, biovars and phylotypes,which are not always internally

consistent for strain differentiation (Agrios, 2005; Geninand Denny, 2012; Hayward, 1991;

Lebeau et al., 2011; Remenant et al., 2010, 2011).Currently, Rs is classified into five races

(R1–R5), five biovars (bv1–bv5) and four phylotypes (I–IV).R1 is endemic to North and

South America and South Asia, while R2 primarily affectsbanana in the tropics. R3 is more

adapted to cooler climates with R3bv2 being highly virulenton potato (S. tuberosum) and

is under strong quarantine measures in the United States.R4 and R5 infect other hosts that

are not as economically significant as Solanum spp. andMusa spp. The race designation is

not based on the traditional gene-for-gene interaction, butrather by primary host range.

Phylotype and sequevar designations as scientificdescriptions are more regularly being

preferred over race (Peeters et al., 2013; Prior et al.,2016). Phylotype I is clustered in Asia;

IIa and IIb contain strains found in the Americas; IIIencompasses the African strains; and

IV are strains from Indonesia, Australia and Japan (Peeterset al., 2013). Phylotypes I, IIb

and III are considered to be the most aggressive.

Tomato resistance to BW is complicated mechanically,physiologically and genetically,

which has provided decades of substantial frustration formany breeders working on

developing disease-resistant genotypes (Acosta et al.,1964; Scott, 2005b). On a positive

note, it has been noted that high levels of resistance arevery hard to incorporate into a

line, but once it has been, it often remains quite durableover time (Acosta, 1978).

Mechanically, resistance to BW involves the restriction ofRs spread within the stem

tissues, both radially and apically, but does not have mucheffect on root and stem

colonization; even the most resistant tomato lines willstill harbour latent infections in the

basal stem under strong disease pressure (Grimault et al.,1994a,b; Grimault and Prior,

1993, 1994a,b; Hayward, 1991; Ishihara et al., 2012;Nakaho, 1997a,b; Nakaho and Allen,

2009; Nakaho et al., 1996, 2000, 2004; Prior et al., 1994,1996). This restriction of spread

leads to a reduction of bacterial population density perunit area of stem (or perhaps more

appropriately, it caps the population density in thetissue). The restriction is specifically

caused by structural reinforcements of the cell wallsaround vessel elements and xylary

parenchyma tissues, and especially the pits and pitmembranes that connect the xylem.

The reinforcing compounds are not entirely known, butinclude the deposition of callose,

lignin and some electron-dense apposition layers along thecell walls. The restriction

appears to only effectively occur in the hypocotyl andabove, rather than in the roots, and

generally prevents the bacteria from spreading out of theprimary xylem tissues and into

the secondary xylem, phloem and pith. Direct inoculation ofthe shoot tissues, however,

tends to bypass or suppress a substantial amount ofresistance action (Danesh et al., 1994;

Thomas et al., 2015). Thus, resistance to foliar wilt isthe result of bacterial containment

measures within the stem following a natural infectionpathway.

Physiologically, environmental factors have plaguedbreeding efforts and genetic

studies of BW resistance (Acosta, 1978; Acosta et al.,1964; Scott et al., 2005b). BW is

strongly influenced by changes primarily in soiltemperature, as well as air temperature,

soil moisture, plant age and inoculum density (Gallegly andWalker, 1949; Mew and Ho,

1976, 1977; Nakaho et al., 1996; Singh et al., 2014; Thomasand Upreti, 2014; Vaughan,

1944; Zehr, 1970). Generally, no disease develops until thesoil temperature rises above

21 °C, while infection may occur as low as 18 °C. From 21to 30 °C, there is a linear

increase of wilting per degree increase in soiltemperature, which plateaus from 30 to

32+ o C. Air temperature effects follow a similar pattern,but are about a magnitude less

severe. A 2 °C difference in average air temperature wasenough to significantly affect the

level of resistance in field-grown tomatoes (Prior et al.,1996). BW is favoured by moist (but

not flooded) soil and inoculum densities greater than 10 6CFUs/mL.

Genetically, BW resistance is polygenic and quantitative innature, and no specific

resistance genes have been verifiably identified so far. Areport identified the known

sources of BW resistance that have fed into the variousbreeding programmes around

the world, along with any known pedigree relationships(Daunay et al., 2010). This report

noted that many seed exchanges took place with poordocumentation in early days of

BW resistance breeding, and it is difficult to accuratelytrace the resistance sources for

all the breeding material. A worldwide germplasm assessmentfor BW resistance tested

lines representing at least 15 sources or combinations ofresistance, and suggested that

the most resistant genotypes overall (>90% wilt) came fromthree locations, which may or

may not reflect their genetic relationships – thePhilippines, the Hawaii tomato breeding

programme and the North Carolina tomato breeding programme(Scott et al., 2005; Wang

et al., 1998). In some cases the resistance source was notknown. CRA66 was another well

studied line with an unknown source of resistance,

exhibiting 85%–87% wilt overall in the

worldwide test.

Assessments of allelic effects for BW resistance are quitediverse. Resistance in ‘Hawaii

7998’ was reported to be controlled by a single dominantgene, and may include several

small-effect loci, but the results were not a great fit tothe model (Scott et al., 2005b).

Similarly, Hawaii 7996 x ‘Floridel’ progeny fit a singledominant gene in 3:1 ratio of

healthy:wilted plants (Grimault et al., 1995). However, thestruggles that breeders have

had with recovering highly resistant progeny indicate thatthe genetics for BW-resistant

lines are not so simple. Using various resistant lines,other researchers have reported

recessive action (Mahir et al., 1993; Monma and Sakata,1993), partial dominance giving

way to recessive later in the season (Acosta et al., 1964),or that resistance is additive due

to lack of compelling evidence otherwise (Acosta, 1978).

For the major sources of resistance that breeders haveworked with, the general

consensus is that there are several major loci or pairs ofloci that confer most of the

resistance to Rs, with multiple small-effect loci providingresistance in a strain-specific

manner (Carmeille et al., 2006; Danesh et al., 1994; Manginet al., 1999; Scott et al., 2005b;

Thoquet et al., 1996a,b; Wang et al., 2000, 2013).Resistance QTLs from the mapping

studies have been identified on chromosomes 3, 4, 6, 8, 10,11 and 12, with chromosome

6 QTL regularly showing the strongest effect over a rangeof strains. ‘Hawaii 7996’ (S.

lycopersicum) is a major source of strong, broad-spectrumresistance that has been used

for most of the QTL mapping studies, which have indicatedthat a large (c. 30 cM) QTL on

chromosome 6 covers four distinct loci (Bwr-6a throughBwr-6d), and another strong QTL

on chromosome 12 (Bwr-12) specific to R1bv3 phylotype Istrains. Bwr-6 appears also to

have a temporal effect, with a shift of relative importancealong the QTL as the disease

advances over time (Mangin et al., 1999), whereas Bwr-12may be specifically linked to

suppression of bacterial multiplication in the stem (Wanget al., 2013). ‘Hawaii 7996’

and the closely related ‘Hawaii 7997’ and ‘Hawaii 7998’lines (derived from PI 127805A)

ranked 1st, 3rd and 5th of the most BW-resistant lines froma worldwide assessment of

international BW-resistant germplasm (Scott et al., 2005b;Wang et al., 1998). The first

mapping study used the resistant parent ‘L285’ (S.lycopersicum var. cerasiforme) (Danesh

et al., 1994).

Molecular markers for BW resistance are desired. AVRDC inTaiwan has reported

simple sequence repeat markers for Bwr-6a through Bwr-6dand Bwr-12 based on the

cross of the susceptible WVa700 and the resistant Hawaii7996 (Hanson et al., 2013; Ho

et al., 2013). A BW resistance derived from ‘T51A’ wasrecently reported to be related

to a caffeoyl CoA 3-O-methyltransferase gene involved inlignin biosynthesis, and SCAR

markers for resistance derived from that line are available(Miao et al., 2008, 2009).

These markers still cover a relative large segment of thegenome containing many gene

loci, so they may not be universal for all strains of thepathogen or other sources of host

resistance.

Breeding efforts have been greatly frustrated by closeassociations of resistance and

small fruit size. Many breeders over the years have workedon breaking this linkage,

without much success. To date, there are no trulylarge-fruited (>200 g fruit weight),

fresh market tomato varieties with high BW resistance, asthe two traits appear to be in

repulsive linkage (Scott et al., 2005b, 2009). This issomewhat strange since the major loci

conditioning fruit size is located on chromosome 2(Grandillo and Tanksley, 1996), which

does not have any mapped BW QTL on it. Pleiotropic effectsbetween BW resistance genes

are possible. In commercial breeding programmes, wiltresistance has been successfully

combined with hybrid rootstocks for grafted vegetableproduction systems, removing the

need to break this linkage; however, public breedingprogrammes have not yet put much

effort into releasing comparable tomato rootstocks so far.The University of Florida tomato

breeding programme has had more success towards combininglarge fruit size and strong

resistance in recent years (Scott et al., 2004). Breedinglines with moderate BW resistance

and medium-large fruit were crossed back to Hawaii 7997 andthen reselected for large

fruit size and high BW resistance in the F2 lines. Thesefamilies were crossed according to

fruit size and resistance level, such that a small-fruitedF5 progeny with high resistance was

crossed with a large-fruited F2 progeny. BW resistance andfruit size selections were made

from F2 to F6. Two F6 selections (8109) were then crossedwith many advanced recurrent

parents and the progeny were selected for healthy growth,BW resistance, fruit size and

yield from F2 to F7. Fla. 8109 is reported to have a meanfruit weight of 203g and disease

resistance levels comparable to the highly resistant‘Hawaii 7997’.

Some final thoughts are as follows: (1) Currently, it isneither clear about how many

unique sources of BW resistance are available nor about howmany of those sources have

been incorporated into modern breeding lines.Investigations along these lines would

be very helpful for breeding lines for BW resistancediversity, which will likely improve

the overall durability of those genetics for long-termeffective management efforts.

(2) Several breeders (Acosta, 1978; Scott et al., 1992;Scott et al., 2005b) have regularly

remarked at the substantial trouble that environmentalvariation, especially temperature,

has had in clouding their genetic analyses, so much so that

it is amazing they did not

give up breeding for BW resistance all together. Much ofthe trouble is related to the

dynamic nature of wilt expression, which is a function ofbacterial activity and primarily soil

temperature. Development of models that can taketemperature effects into account may

be helpful. Alternatively, the development of assessmentmethods for resistance that do

not rise and fall at the whim of the weather are likely toprovide a strong degree of clarity

to the genetic black box of BW resistance expression.

3 Fungal disease resistance breeding

3.1 Botrytis grey mould

Grey mould is caused by the fungus Botrytis cinerea. Thepathogen has more than 200

species of host range including tomato, potato, pepper,bean, onion, cucurbits, crucifers,

berries and ornamental plants. B. cinerea affects all theabove-ground parts of the plant

including stems, leaves and fruits severely (Agrios, 2005).There are several QTL derived

from accessions of wild relatives of tomato such as Solanumhabrochaites LYC4, conferring

resistance to this disease and mapped to tomato chromosomes1 and 9 (Davis et al.,

2009; Finkers et al., 2007a,b). This information may beexploited to develop resistant

cultivars. However, no major genes have been identifiedyet. The control of grey mould

is primarily based on use of fungicides and culturalpractices. No grey mould-resistant

tomato cultivars or varieties have been developed yet.However, resistance to this disease

has been found in some wild species (Egashira et al., 2000).

3.2 Early blight

Early blight (EB), caused by fungi Alternaria linariae(formerly A. solani) and A. alternata, is

one of the devastating foliar diseases of cultivatedtomato. EB pathogens reproduce only

with the asexual cycle and the isolates have high geneticvariation, which helps them to

adapt easily to different environments and overcomefungicide toxicities. EB has caused

major epidemics in North, Central and South America; SouthAsia; and Africa (Foolad et al.,

2008). EB resistance is a complex quantitative traitcontrolled by additive or non-additive

interactions of multiple loci with small effects and GxEinteractions (Barksdale and Stoner,

1977; Martin and Hepperly, 1987; Nash and Gardner, 1988).No single qualitative gene for

EB resistance has been identified so far. Therefore,breeding for EB resistance has been

challenging and so far the approach of variety developmentis totally based on phenotypic

selection. Initially, EB-resistant S. lycopersicumaccession PI138630 was used as a resistant

source to develop other resistant breeding lines 71B2 andC1943. Resistant breeding line

71B2 was resistant to leaf blight but susceptible to collarrot, whereas C1943 was highly

resistant to collar rot, but susceptible to leaf blight(Barksdale, 1969; Barksdale and Stoner,

1977). These two lines were further used for developing

other moderately resistant tomato

breeding lines: NC63EB, NC870, NCEBR-2, NCEBR-3, NCEBR-4,NCEBR-5, and NCEBR

6, along with thehybrids: ‘Plum Dandy’ and ‘MountainSupreme’ (Gardner, 1988; Gardner,

2000b; Gardner and Shoemaker, 1999). Several otherEB-resistant fresh market breeding

lines were released later including NC 1 Grape, NC 2 Grapeand NC 3 Grape, through

phenotypic selection in different filial generations(Gardner and Panthee, 2010a). Similarly,

hybrid tomatoes resistant to EB such as ‘Mountain Magic’and ‘Mountain Supreme’ have

also been released (Gardner and Panthee, 2012a; Gardner andShoemaker, 1999). These

hybrids have proved to be extremely useful to manage thedisease in various parts of the

world.

3.3 Fusarium wilt

Fusarium wilt is a vascular disease of tomato caused by thesoil-borne fungal pathogen

Fusarium oxysporum f. sp. lycopersici (Fol). The disease isinitiated with yellowing of a

leaflet or shoot, followed by wilting and yellowing of moreleaves, dropping of wilted

leaves and ultimately death of plants before maturation.Three races of this pathogen

have been reported as of now, that is, race 1, 2 and 3causing Fusarium wilt in tomato.

Corresponding to this, three Fusarium wilt resistance genesI, I-2 and I-3 have been

identified in S. pimpinellifolium PI 79532, hybrid betweenS. lycopersicum and S.

pimpinellifolium PI 126915, and S. penneli LA716,respectively (Alexander and Tucker,

1945; Bohn and Tucker, 1940).

Since fungicides are not effective to control this disease,the better approach to control

this is to develop a resistant variety containing all threegenes. Several molecular markers

have been developed for MAS of Fusarium wilt-resistantgenes (Tanyolaç and Akkale,

2010). Research efforts are ongoing at North Carolina StateUniversity and University of

Florida to develop resistant varieties. As a result,several resistant breeding lines are now

available, such as Fla 7547 and Fla 7481 that are resistantto races 1, 2, 3 (Scott and Jones,

1995) and hybrids including Mountain Merit (I, I-2, I-3),Mountain Honey (I-3), Mountain

Majesty (I, I-2), Mountain Vineyard (I-3) and Solar fire(I, I-2, I-3) (Panthee and Gardner,

2010b, 2011, 2013a,c; Scott et al., 2006b). Both MAS andconventional breeding methods

were used to develop resistant lines and cultivars.

3.4 Fusarium crown and root rot

Fusarium crown and root rot is one of the serious diseasesof tomato worldwide, both

in greenhouse and field-grown tomatoes, caused bysoil-borne pathogen Fusarium

oxysporum f. sp. radicis-lycopersici (FoRL). The diseasewas first reported in Japan

in 1969 and in California in 1974 (Benhamou et al., 1989).FoRl has a high genetic

variation and wide host ranges including Solanum melongena,

Capsicum frutescens L.,

Arachis hypogaea L., Astragalus glycyphyllos L., Glycinemax. Merr., Phaseolus vulgaris

L., Pisum sativum L., Trifolium spp., Vicia faba L.,Cucumis spp., Beta vulgaris L. and

Spinacia oleracea (Szczechura et al., 2013). Nine differentVCGs (Vegetative Compatibility

Groups) of FoRL have been identified from Western Europe,North America and the

Mediterranean region (Balmas et al., 2005; Katan and Katan,1999). A single dominant

gene Fr1 conferring resistance to FoRL, which is alsopresent in close proximity with the

Tm2 gene conferring resistance to tobacco mosaic virus, hasbeen detected to control

the resistance against FoRL (Vakalounakis, 1988;Vakalounakis et al., 1997). Three RAPD

markers (UBC #’s 116, 194 and 655) and one RFLP marker(TG101) have been developed

to screen tomato lines for the Fr1 gene (Fazio et al.,1999). These markers have been used

to develop resistant lines and cultivars (Tanyolaç andAkkale, 2010). Fusarium crown and

root rot-resistant breeding lines such as Fla 7781 and Fla7775 having the homozygous

Fr1 gene, have been released from the University of Florida(Scott and Jones, 2000). Fla

7775 also contains Tm-2 gene. These lines were developedafter several generations of

single plant selection.

3.5 Grey leaf spot

Grey leaf spot is caused by the fungal pathogen Stemphyliumlycopersici and Stemphylium

solani. The disease is characterized by grey lesions on theleaves. The genetics of grey leaf

spot resistance is controlled by the single incompletelydominant Sm gene and an RFLP

marker associated with this gene has also been developed(Behare et al., 1991). Several

grey leaf spot-resistant breeding lines have been releasedsuch as Fla 7775, Fla 7781 and

Fla 7946 (Scott, 2004; Scott and Jones, 2000).

3.6 Late blight

Late blight (LB), a serious and destructive disease oftomato is caused by the oomycete

Phytophthora infestans (Mont.) de Bary. P. infestansliterally means ‘plant destroyer’ in

Greek. P. infestans originated in the Andean region, whichis also the origin of tomatoes and

potatoes ((Foolad et al., 2008) and was then distributedthroughout the world in all tomato

and potato growing regions. LB was first identified innortheastern United States in 1843

and in different countries of Europe (e.g. France, Belgiumand the Netherlands) in 1845.

The pathogen then spread throughout the world by the earlytwentieth century (Nowicki

et al., 2012). The first screening of several wild speciesincluding S. pimpinellifolium, S.

habrochaites, S. peruvianum and S. chilense along with S.lycopersicum accessions for

the LB resistance was conducted in 1946, after theepidemics in the northeastern United

States (Foolad et al., 2014). P. infestans is a verysuccessful pathogen as it reproduces both

sexually and asexually. Sexual reproduction contributes tothe evolution of more virulent

isolates (Fry, 2008).

P. infestans has two mating types: A1 and A2. The diseasewas not a serious problem

until the 1970s, because sexual reproduction was restricteddue to the geographical

Figure 2 Late blight screening trial in North Carolina. Onleft side of the row, there is a resistant plot

whereas there are multiple plots of susceptible plots onthe right side of the front row. There are

several resistant plots inside the rows.

separation of A1 (outside of Mexico) and A2 (only inCentral Mexico) mating types

(Goodwin et al., 1994). Only US1 was observed inside UnitedStates. However, in the

1990s, new and virulent strains US-7, US-8, US-11 and US-17were detected inside the

United States and Canada (Gavino et al., 2000; Goodwin etal., 1994, 1998). US-8 caused

the epidemics in the United States and Canada during 1993;US-11 destroyed whole

tomato fields in the Pacific Northwest, New York andCalifornia; and US-17 caused another

destruction of tomatoes during the mid-to-late 1990s(Gavino et al., 2000). Again, LB

epidemics occurred in the northeastern parts of the UnitedStates in 2009–2010 driven by

the new strains US-22, US-23 and US-24 (Johnson et al.,2015). Once an outbreak takes

place, it spreads rapidly in the field (Fig. 2).

Both qualitative and quantitative resistances have beenreported in tomato. Three major

genes Ph-1, Ph-2 and Ph-3 have been discovered against LBin closely related wild species

of S. pimpinellifolium and incorporated into cultivatedtomatoes. Ph-1, a single dominant

gene specific to race-0 (T-0) of P. infestans, has beensuccessfully incorporated in cultivated

tomato Nova and New Yorker (Foolad et al., 2008; Nowicki etal., 2013). However, because

of emergence of race T-1, the Ph-1 gene was no longeruseful for LB management.

Ph-2, an incompletely dominant gene conferring partialresistance against T-1 isolates,

has also been incorporated into several fresh market andprocessing tomato varieties

using molecular and conventional breeding approaches(Foolad et al., 2008; Foolad

and Panthee, 2012). However, Ph-2 does not provide a strongresistance against more

aggressive isolates of LB (Goodwin et al., 1995; Moreau etal., 1998).

Not surprisingly, the Ph-2 gene was also overcome by theemergence of new isolates.

Then, a stronger gene (Ph-3) was identified in S.pimpinellifolium accession L3708 at the

Asian Vegetable Research and Development Center in Taiwan(Black et al., 1996). Ph-3

is a partially dominant gene, which has also beenincorporated into several fresh market

and processing tomatoes by using PCR-based markers (Fooladet al., 2008; Foolad and

Panthee, 2012). However, Ph-3 alone couldn’t provideresistance against virulent isolates

such as US-7 and US-17 (Kim and Mutschler, 2006); hence,

the combination of Ph-2 and

Ph-3 is desirable. Several tomato breeding lines such asNC1CELBR and NC2CELBR, and

hybrids – Mountain Magic, Mountain Merit having both Ph-2and Ph-3 genes, and Mountain

Rouge and Plum Regal (Ph-3 gene) have been developed andreleased by North Carolina

State University, using both phenotypic and MAS approaches(Foolad and Panthee, 2012;

Foolad et al., 2014; Gardner and Panthee, 2010b,c; Pantheeand Gardner, 2014). Research

is ongoing to develop markers for the selection of thecombined resistance of Ph-2 and

Ph-3 (Merk et al., 2012).

3.7 Powdery mildew

Powdery mildew is a common disease observed in manyhorticultural crops, caused by

the fungal pathogen Oidium lycopersici and Oidiumneolycopersici. Isolates from North

America belong to O. neolycopersici (Kiss et al., 2005).The disease poses a has high risk to

in greenhouse production, and can develop in the field.Both monogenic and quantitative

resistance for this disease have been identified in wildspecies. The incompletely resistant

genes Ol-1 and Ol-3 were detected in S. habrachaitesG1-1560 and G1-1290, respectively,

and a recessive resistance gene (ol-2) was found in S.lycopersicum var. cerasiforme

(Kashimoto et al., 2003). Similarly, another singledominant resistance gene lv has been

identified in S. chilense (Chunwongse et al., 1994).However, there are not many resistant

cultivars and breeding lines of tomato against powderymildew disease. Some resistant

breeding lines or cultivars include Grace, DRW 4369,Milano, DRW 4409 and Hirol 3-2-2.

The resistant cultivar Grace, which is widely used inEurope, is highly susceptible to the

Japanese isolate of O. neolycopersici (Kashimoto et al.,2003).

3.8 Septoria leaf spot

Septoria leaf spot (SLS), one of the major fungal diseasesof tomato, is caused by Septoria

lycopersici, which is common in tropical and subtropicalregions with high humidity.

Originally, the disease was reported in Argentina in 1882,while in the United States, it

was first reported in 1895 (Seymour and Ridings, 1980). SLSis characterized by small

water-soaked spots on leaves, stems, calyx, blossoms andrarely on fruits. Sources of SLS

resistance has been detected in S. pimpinellifolium.Selection for SLS resistance is mainly

based on phenotypic screening. Three RAPD markersassociated with SLS resistance and

two RAPD markers linked with SLS susceptibility have beenidentified, which could be

useful for future tomato improvement programmes using MAS(Joshi et al., 2015). There

are no commercial varieties resistant to SLS at present.Recently, however, the cultivar Iron

Lady was developed by Cornell University that is resistantto SLS, EB and LB (Zitter et al.,

2011).

3.9 Verticillium wilt

Verticillium wilt in tomato is caused by the soil-bornefungi Verticillium albo-altum and

V. dahlia. The pathogens have wide host ranges, infectingover 200 species, including

tomatoes, potatoes, eggplant, strawberries, blackberries,raspberries, artichoke, beet,

broad bean, chicory, cucumber, dandelion, endive,horseradish, muskmelon, okra, peppers,

radish, rhubarb, salsify and watermelon, which increasesthe longevity of the pathogen in

the soil. Additionally, the resting spore of the pathogens(microsclerotia) also allows them

to overwinter in the soil. The disease causes wilting,chlorosis, necrosis, stunting and vein

clearing on susceptible hosts. Verticillium spp. alsoproduces phytotoxins and cell wall

degrading enzymes making the disease more complex (Sherf,1980).

Fumigation for this disease is not very effective, and thedisease affects the vascular

tissues. Therefore, the deployment of resistant andtolerant tomato cultivars and lines

would be the best approach to control this disease. Theresistance to Verticillium wilt is

controlled by the single dominant locus Ve, which containstwo tightly linked and inversely

oriented genes – Ve1 and Ve2 (Diwan et al., 1999; Kawchuket al., 2001). The Ve locus is

effective against race 1 of V. albo-atrum and V. dahlia.Molecular markers such as CAPS,

SNPs and InDels have been developed for the selection ofVe1 and Ve2 genes (Jung et

al., 2015).

Several Verticillium wilt-resistantt cultivars areavailable with good horticultural traits. For

example, Jumbo Wonder Boy, Rutgers 39, Ultra Boy, UltraGirl and Rushmore among others

(Sherf, 1980). Similarly, several breeding lines includingFla 7547, Fla 7481, Fla 7781, Fla

7775, Fla 7946 (Scott and Jones, 1995, 2000; Scott et al.,2006b) and hybrids Carolina

Gold, Sun leaper and Plum Dandy (Gardner, 2000a,b,c)resistant to Verticillium wilt have

been developed. These lines and hybrids were developedthrough traditional breeding

approaches. Almost all recently developed breeding linesand hybrids from NC State

tomato breeding programme have Verticillium wilt resistancein their genetic background.

Deployment of lines carrying Ve have revealed the presenceof Verticillium strains that

are able to overcome Ve and have collectively been labelledrace 2, although it is not

clear what is the genetic makeup of the population in theecosystem. In other words, race

2 may be different between the United States, Brazil,Europe, Japan and elsewhere. So a

regional breeding strategy is needed to effectively combatthe disease in each respective

growing region. A few lines have been reported to havequantitative resistance to race

2 strains – IRAT-L3 and FARAKO-BA; IRAT-L3 does not carryVe for race 1 (Baergen and

Hewitt, 1988; Baergen et al., 1993; Gold et al., 1996).

4 Virus disease resistance breeding

4.1 Cucumber mosaic virus

Cucumber mosaic virus (CMV) is an aphid-transmitted diseaseof tomatoes in temperate

regions. Infected plants are yellow, bushy and stunted withpatches of different colour. Severely

infected plants are distorted with shoestring-like shapes.In certain tomato growing areas, CMV

is considered one of the most destructive viral diseases oftomato. Although resistance to CMV

has been reported in wild species such as S.pimpinellifolium, S. habrochaites, S. cheesmaniae,

S. chilense and in S. lycopersicoides (Scott, 2007), nocommercial resistant cultivar has been

developed yet. Transgenic approaches have been used tointroduce and express resistance

genes from these sources in various studies (Anfoka, 2000;Cillo et al., 2004; Ntui et al., 2013;

Pratap et al., 2012). There are no existing usefulmolecular markers reported for MAS.

4.2 Potyviruses

The tobacco etch virus (TEV) and potato virus Y (PVY) aretwo common potyviruses affecting

tomatoes in tropical and subtropical regions, particularlyin southeastern United States

and in Turkey (Celebi Toprak et al., 2009; Li et al.,2012). Sources of resistance to TEV

have been reported in the tomato wild species S.pimpinellifolium, S. habrochaites and S.

pennellii (Scott, 2007). However, there is no report of anycommercial cultivar of tomato

with resistance to TEV. A recessive resistance locus(pot-1) was identified in S. habrochaites

accession PI 247087, which reportedly confers resistance toboth TEV and PVY (Parrella

et al., 2002). However, no useful molecular markers havebeen reported to use for MAS.

4.3 Groundnut ringspot virus

Groundnut ringspot virus (GRSV) is a member of tospovirusinfecting tomato plants. This

was reported for the first time in Florida in 2010,although its symptoms were observed

for several years. Symptoms include necrotic flecks andspots, irregular chlorotic areas and

deformation of leaflets (Webster et al., 2010). GRSV wasoriginally described in peanut

in South Africa and in tomato from Brazil but has morerecently been reported infecting

peanut in Argentina and soya bean (Glycine max) in SouthAfrica (Pappu et al., 2009). The

relatively narrow reported host range of GRSV is incontrast to the extremely wide host

range of TSWV. GRSV is transmitted exclusively by thripsincluding the western flower

thrips (Frankliniella occidentalis Pergande), F. schultzeiTrybom and F. gemina Bagnall

(Pappu et al., 2009). There are no reports of resistanttomato cultivars to GRSV.

4.4 Tomato chlorotic spot virus

Tomato chlorotic spot virus (TCSV) is also a member ofTospovirus. It was first reported

from Florida in 2012 (Londono et al., 2012). Recently, itwas also reported in Ohio (Baysal

Gurel et al., 2015). Its symptoms include necrosis anddeformation of the whole plant.

There is no reported variety improvement for TCSV.

4.5 Tomato mosaic virus

Tomato mosaic virus (ToMV), a Tobamovirus closely relatedto tobacco mosaic virus

(TMV), has a wide host range that includes tomato, tobacco,pepper, ornamentals and

several weed species (He et al., 2012). Reports suggestthat over 800 plant species may

serve as alternative hosts to ToMV (Alexander, 1971).Although it is a serious problem

throughout the world, it is particularly troublesome forgreenhouse tomato production. It

is an RNA virus that is highly stable under naturalconditions and conducive to mechanical

transmission (Alexander, 1971) such as routine planthandling in field or greenhouse

operations (Park et al., 1999; Sacristan et al., 2011).Leaves of ToMV-infected plants

display light green or yellow mottling, with roughdownturned edges and a shoestring

like elongation on young growth (Fig. 3). Plant growth maybe stunted, with poor fruit set

and small, brown-streaked fruit (Jung et al., 2002; Park etal., 1999). Often, it is difficult to

distinguish between symptoms of nutrient deficiency andToMV on younger leaves.

Resistance to the disease has been reported in wildrelatives of cultivated tomatoes

such as Solanum peruvianum (Alexander, 1971; Scott, 2007).Three major resistance

genes have been reported in this wild relative: Tm1, Tm2and Tm2 a or Tm2 2 (Hall, 1980;

Young et al., 1988). Among these genes, Tm2 a is the mostwidely deployed in breeding

programmes as it confers resistance to most of the ToMVstrains. Whereas this gene

has been introgressed into several tomato breeding linesand varieties, combining this

gene with other virus resistance is an ongoing process intomato breeding programmes

Figure 3 Typical symptom of tomato mosaic virus in tomatoleaves. The yellow veins are apparent on

young leaves.

(Garcia-Martinez et al., 2012). Screening early generationbreeding material based on

ToMV phenotypic data is challenging. As an RNA virus, ToMVcan remain stable for several

years and be transmitted by both mechanical means andthrough seed. Therefore, it

has the potential to spread quickly to production areas andbecome a major concern

to the industry and breeding programmes. The use ofreliable molecular markers for

early generation screenings has been employed (Panthee etal., 2013; Shi et al., 2011)

to reduce the need to rely on inoculation of isolated largepopulations, which has

substantially reduced the time and cost of producingsuperior resistant cultivars. Several

ToMV-resistant fresh market hybrids are being evaluated inour breeding programme at

North Carolina State University.

4.6 Tomato spotted wilt virus

Tomato spotted wilt virus (TSWV) is a member of the genusTospovirus, which belongs to

the family Bunyaviridae (Gordillo et al., 2008; Soler et

al., 2003). TSWV has a wide host

range that includes tomato, tobacco, pepper, potato,celery, pea, peanut, dahlia, lettuce,

chrysanthemum, gerbera, iris and impatiens, among others.TSWV has been reported

in over 800 plant species (Saidi and Warade, 2008) and is aserious problem throughout

the world, particularly in warm, tomato producing regions.The estimated annual global

crop loss due to TSWV in the world is $1.0 x 10 9(Goldbach and Peters, 1994). TSWV is

transmitted by thrips, particularly western flower thrips(WFT: Frankliniella occidentalis) in the

family Thripidae (Ullman et al., 1997). Under naturalconditions, the magnitude of the TSWV

problem is directly proportional to the thrips population(German et al., 1992; Goldbach

and Peters, 1994). TSWV-infected tomato plants developchlorotic and necrotic ringspots on

their leaves, which affects the overall yield and qualityof the fruit, becoming unmarketable.

Resistance to TSWV has been reported in wild relatives suchas Solanum peruvianum

(Rosello et al., 1998; Soler et al., 2003), S.pimpinellifolium (Saidi and Warade, 2008),

S. habrachaites (Maluf et al., 1991) and in S. chilense(Canady et al., 2001). The TSWV

resistance gene was first introduced into the cultivatedtomato variety ‘Stevens’ in

the1960s (Stevens, 1964; Stevens et al., 1994). Using thisvariety as a source, the gene

was further introgressed into several tomato varieties andbreeding lines. Recently, the

resistance gene (Sw-5) was introgressed into fresh marketbreeding lines of tomato

(Gardner and Panthee, 2012b). Furthermore, Sw-5 gene hasbeen successfully deployed

into large fruited tomato hybrids including Mountain Merit,Mountain Majesty and

Rebecca (Panthee and Gardner, 2010a, 2011; Scott et al.,2009); plum hybrid Plum

Regal (Gardner and Panthee, 2010c); and grape hybridsMountain Honey and Mountain

Vineyard (Panthee and Gardner, 2013a,b) During the courseof the development of TSWV

resistant breeding lines, it became apparent that screeningbreeding material for TSWV

resistance using phenotypic data was extremely difficultbecause the symptoms are not

expressed uniformly throughout the plant. This lack ofuniformity may lead to misleading

results in screening trials. Furthermore, breeders have torely on natural field inoculum

for screening, which may not be uniform throughout theexperimental plot (Soler et al.,

2003). Such variations in inoculum density may also producemisleading results. Use of

DNA-based molecular markers for a resistance gene screeningoffers an alternative for

both of these problems. Novel molecular markers have beendeveloped and utilized for

the screening of Sw-5 gene in tomato breeding lines, whichhave been found extremely

useful (Panthee and Ibrahem, 2013).

4.7 Tomato yellow leaf curl virus

Tomato yellow leaf curl virus (TYLCV), a begomovirus of the

geminiviridae family

transmitted by whitefly, is a serious disease of tomatoesin tropical and subtropical regions

of the world. Genetic sources of resistance have beenidentified in the wild relatives of

tomato including S. pimpinellifolium, S. peruvianum, S.cheesmania, S. habrochaites and

S. chilense (Scott, 2007). Thus far, six resistance loci,Ty-1, Ty-2, Ty-3, Ty-4, Ty-5 and Ty-6

have been identified and mapped to tomato chromosomes 6, 11and 3. (Anbinder et al.,

2009; Chague et al., 1997; Ji et al., 2009a,b; Zamir etal., 1994). Ty1 and Ty3 are allelic

to each other, which were derived from S. chilense (LA1932AND LA1938) (Verlaan et

al., 2013). Due to the very destructive nature of thisdisease in certain tomato growing

regions, intensive breeding efforts have been devoted todeveloping TYLCV-resistant

cultivars. However, no completely resistant cultivars havebeen developed as of now,

although breeding lines with one or more genes have beendeveloped such as UMH 1200,

UMH 1203, Fla 8624, Fla 8638B and Fla 8923 (Garcia-Martinezet al., 2011, 2012; Hutton

et al., 2015; Scott et al., 2015a).

5 Nematode resistance breeding

Nematodes are soil-borne animal pathogens of plants thathijack plant roots for food

and reproduction. The most economically concerning nematodepathogens for tomato

are the sedentary endoparasites root-knot nematode(Meloidogyne spp.; RKN) and cyst

nematode (Globodera spp.; CN), which manipulate hostfunctions for the benefit of the

worm. The primary differences between RKN and CN arerelated to the type of feeding

site they initiate – Giant cells (RKN) or syncytia (CN) –as well as forming a root gall (RKN)

or having the body mostly outside the root that becomes acyst (CN). Nematode damage

is primarily caused by disruptions in plant rootsource–sink relationships and the disruption

of normal root function for water and nutrient uptake (Abadet al., 2009). Common

management strategies include soil fumigation, croprotation and deployment of host

resistance (Agrios, 2005).

Plant resistance to nematode infection is commonly definedas supporting low or no

nematode reproduction (Cook and Evans, 1987; Roberts, 2002,2004). Many aspects of

nematode parasitism and resistance genetics can be found intwo excellent reviews (Abad

et al., 2009; Williamson and Roberts, 2009). Resistance isconferred by specific genes in the

host population. Non-host resistance, however, is relatedto a broader lack of host traits that

are required for nematode parasitism and reproduction.Resistance genes work because

they block or suppress various aspects of the nematodereproductive cycle in response to

infection. Root gall development is suppressed orcompletely lacking depending on the

resistance genetics of the host, although some plantgenetics have been identified that

reduce galling but do not affect nematode reproduction(Garcia et al., 1996; Roberts et al.,

2008). In order to reproduce, juvenile nematodes must beattracted to the host plant root,

penetrate the root, migrate through the root cortex,establish a feeding site in the vascular

parenchyma and accumulate sufficient nutrition for growthand egg laying (Abad et al.,

2009). Most effective resistance mechanisms do not preventthe initial root penetration

step, but instead work downstream of that event. Therefore,tolerance to root penetration

(little to no host damage or crop loss in response tonematode infection) is essential for

effective genetic resistance to occur, otherwise hostresponses (such as root-based HypR)

often lead to greater root damage and stunting (Williamsonand Roberts, 2009).

The genetics of nematode resistance in crop plants arevarious, with cases of resistance

being conferred by single major genes or combinations ofseveral genes or QTLs

(Williamson and Roberts, 2009). Resistance gene expressionmay be dominant, recessive

or additive, and multiple resistance genes may actconcurrently in the host plants. Most of

the plant nematode resistance genes have been identified inwild relatives, and therefore

must be introgressed into cultivated species. The use ofgenetic mapping techniques,

as well as the successful cloning of multiple nematoderesistance genes in tomato has

led to the development of DNA- and gene-based markers that

can aid breeding efforts

either in gene introgressions or genetic transformation(Caromel and Gebhardt, 2011).

In total, six nematode resistance genes have been cloned,two of which have been in

tomato. Nematode and host–plant interactions involve theinteractions between pathogen

and host compounds like in other plant diseases. Generally,it involves the same systems

such as pattern-recognition receptors (PRRs), effectors andso on, but breeders should be

cautious because the nematode components are not perfectlyanalogous to those in fungi

and bacteria, although the same terminology is used for allthree groups. Race structures

have been applied to nematode populations, but they may nothave the same biological

meaning as in the other plant pathogen groups. Severalexcellent reviews of nematode

resistance in plants are available (Caromel and Gebhardt,2011; Williamson and Roberts,

2009).

5.1 Potato cyst nematodes

Potato cyst nematodes (PCN) encompass two species:Globodera rostochiensis (Gr) and

G. pallida (Gp). These nematode populations have beengrouped into pathotypes based

upon the ability of the group to grow on potato clones withspecific resistance genes

(Brodie, 1998; Phillips, 1994). Gr is grouped into fivepathotypes (Ro1–Ro5), whereas Gp

has several (Pa1, Pa2/3) (Sobczak et al., 2005).

Host resistance to PCN tends to decrease the nematodepopulation, rather than directly

targeting the worms, which remain virulent on resistanthosts (Sobczak and Golinowski,

2011). Resistance is often expressed by the developmentalrestriction and subsequent

collapse of syncytia in the roots a few days afterdevelopment has begun, which is

usually only enough time for male worms to develop, notfemales, thereby reducing the

reproduction levels of the infecting population. This typeof resistance response has been

termed the ‘delayed hypersensitive response’ (Sobczak andGolinowski, 2011).

Breeding for resistance to Gr has been rather successfuldue to the identification of

single-gene resistance that has remained quite effectiveover many years and acres planted,

whereas breeding for resistance to Gp is more difficultbecause it is more quantitative

with oligogenic inheritance patterns (Caromel and Gebhardt,2011). Pockets of Gr that

can overcome the resistance do occur. The Hero gene on theshort arm of chromosome

4 provides broad-spectrum resistance against all Grpathotypes and partial resistance

against Gp (only the pathotypes Pa2/3) (Ernst et al., 2002;Ganal et al., 1995). The gene

was introgressed from S. pimpinellifolium LA 1792 and hasbeen cloned. Hero encodes

a CC-NBS-LRR class protein, which is typical of manysingle-gene resistances, and is part

of a multi-gene family. Curiously, transgenic potato plantscarrying the Hero gene are not

resistant to potato-infecting strains of PCN (Sobczak etal., 2005).

5.2 Root-knot nematodes

RKN afflict many crop species, and six species arepathogenic on solanaceous crops –

Meloidogyne arenaria, M. incognita, M. javanica in moretropical regions and M. hapla,

M. fallax and M. chitwoodi in more temperate regions(Caromel and Gebhardt, 2011).

The tropical species are the typical pathogens of tomato(Williamson and Roberts, 2009).

Resistance gene-based race grouping is not a commonpractice for RKN.

Resistance to RKN is conferred by single genes that respondto specific virulence factors

secreted by the worm, initiating a signalling cascade thatleads to a HypR that prevents

successful root colonization (Jones and Goto, 2011). S.arcanum and S. peruvianum are

major sources of resistance for RKN in tomato. In thetomato germplasm there are nine

resistance genes available (Mi-1 through Mi-9) (Caromel andGebhardt, 2011; Williamson

and Roberts, 2009). These genes are dominantly expressedand confer major gene

resistance, although different genetic backgrounds mayexpress epistatic interactions

from modifier loci. Three of these genes have been mapped,with Mi-1 and Mi-9 residing

on chromosome 6 and Mi-3 on chromosome 12. This is thereason breeders have had

troubles combining BW resistance and TYLCV resistance(Ty-1) with Mi-1, especially in the

early days of resistance breeding (Scott, 2005b).

The first tomato nematode resistance gene that was clonedwas Mi-1, which is one of

three variants with Mi-1.2 being the functional gene thatinitiates the HypR, and is the only

one that is available in the cultivated tomato germplasm(Milligan et al., 1998; Rossi et al.,

1998; Vos et al., 1998; Williamson and Roberts, 2009). Likethe PCN resistance gene Hero,

Mi-1 belongs to the NBS-LRR (nucleotide-bindingsequence–leucine-rich repeat) class of

resistance gene, which are typically associated withqualitative resistance and hypersensitive

responses (Boller and Felix, 2009). The gene is associatedwith strong reductions in root

galling and strangely confers resistance to several insectpests (Caromel and Gebhardt, 2011;

Williamson and Roberts, 2009). Mi-1 was introgressed fromS. peruvianum in the 1940s, and

has been widely deployed for many decades with surprisinglygreat success. However, the

gene has a curious problem of becoming ineffective whentemperatures rise above 28 °C

(Williamson, 1998), but does recover over time (Nasu etal., 2015). The DNA-based marker

REX-1 is available, and continues to be diagnostic inadvanced breeding lines (Caromel and

Gebhardt, 2011). Despite it still being a very useful gene,nematode populations around the

world can and have developed the ability to overcome theresistance (Verdejo-Lucas et al.,

2009; Williamson, 1998). Mi-9 from S. arcanum appears tohave the same broad-spectrum

resistance as Mi-1, but does not exhibit the sensitivity tohigh temperatures (Caromel and

Gebhardt, 2011). Introgression of other Mi genes isdifficult due to sexual incompatibility

issues, although embryo rescue techniques have allowed Mi-3to be transferred to S.

lycopersicum, which is able to provide resistance againststrains of M. incognita that

overcome Mi-1 (Yaghoobi et al., 1995) and M. javanica(Williamson and Roberts, 2009).

6 Genetic engineering for developing disease-resistant

tomatoes

The development of molecular tools and markers in the early1980s led to the identification,

cloning and characterization of genes underlying manydesired traits, including genes

involved in defence mechanisms in tomato (Punja, 2001).Most of the disease resistance

genes in tomato have been discovered in wild tomatoes. Theintrogression of those

resistance genes from wild tomatoes into cultivated linesthrough conventional breeding

methods is often associated with the negative horticulturalcharacteristics carried along by

linkage drag from the wild tomatoes. Therefore, geneticengineering (strictly, the method

is called the cisgenic approach if transferring the genesfrom wild relatives of tomato using

a transgenic method) in the specific introgression ofresistant genes from wild tomatoes

into cultivated tomatoes without any linkage drag (Akhondand Machray, 2009; Jacobsen

and Schouten, 2008; Kuhl et al., 2007; Mondal et al., 2016).

The history of transgenic tomato traces back to the early1990s, when the transgenic

‘FlavrSavr’ tomato with extended shelf life was developed,allowing tomatoes to ripen

on the vine and hence increasing the flavour of tomatoes(Kramer and Redenbaugh,

1994). While the shelflife was effectively extended, therewere negative impacts on

flavour, which led to a lack of acceptance by the market.Thereafter, genetic engineering

tools were also utilized to obtain disease-resistanttomatoes. For instance, reduced

disease severity due to Fusarium oxysporum f. sp.lycopersici through the combined

expression of chitinase and b-1,3-glucanase (Jongedijk etal., 1995; Vandenelzen et al.,

1994); reduction of Verticillium dahliae races 1 and 2through the expression of hydrolytic

enzymes such as chitinase from wild tomato (Tabaeizadeh etal., 1999); reduction of

P. infestans lesions through the expression of phytoalexinssuch as grape stilbene

(resveratrol) synthase (Thomzik et al., 1997); decrease insize and number of lesions due

to A. solani through the expression of an antimicrobialcompound (Parashina et al., 2000);

slower growth rate of Botrytis cinerea through theexpression of pear polygalactouronase

inhibiting protein (inhibits pathogen virulence products)(Powell et al., 2000); increased

resistance to Sclerotina sclerotiorum through theexpression of Collybia velutipes

oxalate decarboxylase (Kesarwani et al., 2000); TYLCVresistance through the expression

of TYLCV replication-associated gene sequences (Fuentes etal., 2016; Singh et al.,

2015; Yang et al., 2004). Transgenic tomato for othergroups of viruses (tospovirus and

geminivirus) have also been developed (Kumar et al., 2012;Peng et al., 2014; Pratap et

al., 2012; Yang et al., 2014). Oldroyd and Staskawicz(1998) showed the induction of Pto

and Fen pathways leading to systemic acquired resistancethrough the overexpression of

Prf gene, suggesting the role of transgene-induced systemicacquired resistance (SAR)

to achieve broad-spectrum disease resistance. Bacterialspot of tomato, which does

not have an effective resistance despite significantefforts by various tomato breeding

programmes, did not develop in the transgenic tomatocontaining the Bs-2 gene from

pepper after a series of experiments (Horvath et al., 2012,2015; Sendin et al., 2012; Tai et

al., 1999a). Similarly, the level of bacterial speck hasbeen reduced in transgenic tomatoes

using the Pto gene (Chang et al., 2002; Koc et al., 2007).Park et al. (2004) transformed

tomato plants to synthesize glycinebetaine to improvechilling tolerance. Similarly, Lin

et al. (2004) reported the broad-spectrum resistance intomato against tobacco mosaic

virus, BW, bacterial spot, Fusarium wilt and grey leaf spotthrough the expression of

Arabidopsis NPR1 (nonexpressor of PR) gene in tomato. Chanet al. (2005) demonstrated

the enhanced resistance to BW and Fusarium wilt intransgenic tomatoes engineered with

Arabidopsis thionin (Thi 2.1 ) gene.

However, there are several challenges for the developmentand adoption of genetically

modified tomatoes – the success rate of obtainingtransgenic plants, which is very low

(1–10%); cells might get damaged through the high levels ofexpression of engineered

products such as thionins, growth regulators, peroxidaseand elicitor molecules; the need

of tissue-specific promoters when only specific tissues ofplants are targeted for genetic

engineering; the risks of transfering the transgenes toweed relatives; chance of negatively

affecting beneficial microorganisms; and the potentialrisks of human health (Punja, 2001).

Additionally, most of the cis- or trans-genic tomatoeslines have not been tested in the

field environment, often due to costs or regulatoryconstraints, making their true efficacy

uncertain. And on top of everything else, geneticallymodified horticultural crops have

not still reached the point of worldwide approval orauthorization, so even if the ideal

genetically modified tomato were created, it might berejected by the production and

consumer markets or regulatory agencies.


Outbreaks of new diseases, or the evolution of a new raceof a pathogen for any crop plant,

including tomato, is a continuous process. To combat the

problem, identification of the

source of resistance and discovery of resistance allelemust also be a continuous process.

Although the evolution of new diseases or a new pathogenraces is reported through

the publications of the American Phytopathological Society(http://www.apsnet.org/

Pages/default.aspx), new gene or allele information ismaintained by through the Tomato

Genetics Cooperative Reports(http://tgc.ifas.ufl.edu/onlinevo.htm) or the SolGenomics

network (https://solgenomics.net/). Those who areinterested in keeping up-to-date on

tomato diseases and gene/germplasm developments would bewell-advised to regularly

consult these resources.


Significant progress has been made towards the improvementof tomato cultivars for

some bacterial, fungal, viral and nematode diseases. Withthe incorporation of MAS, the

rate of improvement over time has been enhanced. Still,breeding for disease resistance

in tomato can be quite challenging, with positive gainsbeing slow and arduous. Several

overall challenges standout in the literature and includethe following: (1) Resistance

breeding efforts must focus on the quantitative nature ofthe host–pathogen interactions,

focusing on moving as many resistance QTLs as possible.Introgressing resistance

sources into multiple lines to generate moderatelyresistant breeding material, which

are then crossed among each other before being moved intothe inbreeding pipeline,

has shown promise for QTL consolidation into adaptedbreeding material. Making

use of QTL-based resistance, including pyramiding withsingle-gene immunity, may

be very beneficial for improving the overall durability ofthese diseases’ resistances in

tomato over the long term. (2) Most of the bacterialresistance sources harbour latent

infections to various extents (BC and BW), which areimportant to account for when

screening for resistance. The foliar pathogens producesymptoms that are difficult to

accurately quantify, particularly with the human eye (BC,BSP, BSX, EB, Verticillium wilt,

etc.). Accurate phenotyping is essential for genome-basedbreeding of any kind, and

breeders should give added consideration to methodologies,standards and alternative

phenotyping strategies, particularly those that captureseverity on a plant basis rather

than simple per centincidence. (3) Due to the nature of thegenotype x environment

interactions, high levels of phenotypic variance are commonin experiments dealing

with bacterial disease resistance, making statisticallysignificant differences difficult to

detect, especially when trying to measure the effects ofeach contributing loci. Even

small changes in environmental variables, particularlytemperature and moisture, can

wreak havoc on experimental analyses. It may be worthwhile

for breeders to consider

assessment models that are able to specifically account forvariation associated with each

major environmental factor, so that the true geneticeffects can be isolated. (4) Breeding

tomatoes for resistance to nematodes had good success, somuch so that breeders

have often not worked to incorporate new sources ofnematode resistance since Mi-1,

which means that genetic gains have stalled for many years,allowing the build up of

populations that overcome Mi-1. Eight other genes areavailable, with Mi-9 likely being

the closest to incorporation into cultivated tomato. Withthe cloning of several nematode

resistance genes, MAS will be very helpful in backcrossbreeding for rapid and efficient

trait introgression. Maintaining the durability of theseresistance genes is very important,

and tomato breeding would greatly benefit from theconcurrent introgression of multiple

unique genes for gene pyramiding deployments.

In compiling this review, the breeding work of Dr. JamesGilbert that resulted in the

Hawaii 7900 series of lines has proved extremely valuablefor modern efforts in breeding

tomatoes for bacterial resistance, enduring as some of thestrongest and most durable

resistance sources for multiple bacterial pathogens (Scott,2005a,b). For those of us working

with the same material today, we simply wish his breedingnotes on the development of

those lines were a little more thorough. Whether it was a

matter of keen foresight or

simple providence, his selections continue to positivelyimpact our modern-day efforts for

breeding disease-resistant tomatoes. The entire tomatoindustry has greatly benefitted

from his patient work. In a similar fashion, the breedingwork of Dr. Randy Gardner at North

Carolina State University, and Dr. Jay Scott at theUniversity of Florida has had a substantial

impact on global tomato production and disease resistancebreeding on several major

diseases. Future tomato breeders have a legacy to uphold,so let us all work carefully and

wisely to develop and protect the future of the globaltomato industry.

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18 Chapter 18 Integrated weed managementin tomato cultivation

1 Introduction

Weeds have long been recognized as a source of considerableeconomic loss in agriculture.

Weeds cause not only crop yield losses due to competitionfor resources (i.e. light, water

or mineral nutrients) but also a reduction in crop qualityand harvesting efficiency (Zimdahl,

2004). Moreover, weeds may also host pests and pathogensthat can be detrimental to the

health of the crop (Wisler and Norris, 2005).

Integrated weed management (IWM), a component of IntegratedPest Management

(IPM), combines the use of indirect (i.e. preventivemeasures and agronomic practices) and

direct (i.e. physical, mechanical, biological and chemicalmethods) weed control strategies

(Liebman and Davis, 2000; Bàrberi, 2002; Tei and Pannacci,2008, 2016; Sanyal et al.,

2008; Singh et al., 2010). IWM basically consists of threephases:

1 weed population management

2 decision making and

3 direct weed control

These stages are discussed below.

Weed population management is based on the adoption ofpreventive and agronomic

practices and involves both

a) crop management (e.g. cultivar selection, plantingmethod, spatial arrangement) aimed to have a highcompetitive ability of the crop against weeds (Zaragoza,

2003) and

b) weed soil seedbank management by adequate crop rotation,soil tillage and reduction of weed seed disseminationaimed at reducing weed seed reserves in the soil andinfluencing soil seedbank composition (Buhler et al., 1997;Blackshaw et al., 2007).

Decision making is the phase to find an answer to the mainquestion of IWM: Is there

a necessity to directly control the weeds in a given cropor crop rotation? If yes, when?

Where? How? Adoption of weed competition thresholds andmodels is crucial to this

approach (Sattin and Berti, 2003). In other words, the‘decision making’ phase should

consider strategic decisions (i.e. weed control based onthe whole crop rotation instead of

only on one-year crop cycle), tactical decisions within onecropping period (i.e. using weed

density and critical period thresholds) and operationaldecisions (i.e. when and with what

methods to control the weeds).

Direct weed control is based on the integration ofdifferent weed control methods (i.e.

physical, mechanical, biological and chemical) in order toobtain a desired level of control

with a reduced use of herbicides.

The basic aim of IWM in low-external-input and organicfarming systems is, therefore,

both to reduce the effect of weed interference on crops, tomaintain or increase the

diversity and stability of weed populations, and to reducethe dependence on herbicides

and their negative effects (Liebman et al., 2003). So, theIWM links weed control to a

larger picture of agroecosystem management (Sanyal et al.,2008). The IWM system is

fundamental for vegetable crops, including tomato, morethan for other crops (i.e. wheat,

maize, rice), because of their high value, intensivecultivation, lack of competitiveness and

relatively less availability of approved herbicides (Teiand Pannacci, 2016).

2 Weed communities: the target

Weed communities represent a dynamic component ofagroecosystems: the composition

of the weed flora varies from location to location inrelation to the environment (i.e. climatic

conditions, soil characteristics) and cultural practices(i.e. soil tillage, planting method and

time, crop rotation, efficacy and efficiency of weedcontrol methods applied).

Weed community composition and abundance need to bethoroughly studied in order

to build effective and efficient short- and long-term IWMsystems (Jordan and Jannink,

1997). Indeed, in comparison with conventional weedmanagement systems based on

herbicides, the IWM systems, based on reducing (low-inputsystems) or eliminating

(organic farming systems) the use of herbicides, need to besite specific and require more

attention in the choice and combination of technicaloptions and on their effect on single

weed species and on weed community composition (Liebman etal., 2003). So in each crop

and agroecosystem, it is particularly important to assessthe most frequent and abundant

species, the main target of IWM (i.e. key weeds), and thosespecies that could become

important in the future, thanks to their biological andecological characteristics.

Surveys carried out in the Mediterranean Area (e.g. France,Italy, Israel, Morocco,

Poland, Portugal, Spain) (Zaragoza et al., 1994), USA (e.g.in Indiana: Hillger et al., 2006b;

in California: Lanini et al., 2014), Canada (Alex, 1964),Brazil (e.g. Estados de Goiás, São

Paulo, Minas Gerais) (Ronchi et al., 2010), and Asia(William and Chiang, 1980) showed that

the weed communities both in processing and in fresh markettomato crops are commonly

rich in both broad-leaved and grass weed species. In Italy(e.g. Pianura Padana centrale,

Ferrarese, Marche litoranee, Foggiano, Brindisino,Tarantino), for example, Viggiani et al.

(1998) recorded 130 species belonging to 34 botanicalfamilies with about 40 main weeds.

Tei et al. (2003), in a survey conducted by the EuropeanWeed Research Society (EWRS)

Working Group ‘Weed Management Systems in Vegetables’,reported that the weed

flora in processing tomato crops is made up of a smallgroup of common species [i.e.

Echinochloa crus-galli L. (Beauv.), Amaranthus spp.,Chenopodium album L., Polygonum

spp., Portulaca oleracea L. and Solanum spp.] throughoutthe Mediterranean Area

(Table 1). In early direct-sown crops and also intransplanted crops in Central-Northern

Europe, early-emergence weeds like Alopecurus myosuroides

Huds., Lolium spp., Phalaris

spp., several species of Cruciferae (e.g. Sinapis arvensisL., Capsella bursa-pastoris (L.)

Medicus, Raphanus raphanistrum L., Thlaspi arvense L.,Coronopus squamatus (Forskal)

Ascherson) and Asteraceae (e.g. Matricaria chamomilla L.,Senecio vulgaris L., Sonchus

spp. Cirsium arvense (L.) Scop., Galinsoga parvifloraCav.), and other species like Fumaria

officinalis L., Anagallis arvensis L., Stachys annua L.,Lamium spp. and Veronica spp. are

frequent and important (Table 1).

The species belonging to Amaranthus and Chenopodium gendersare numerous

and their relative importance among the countries is prettydifferent: A. retroflexus L.

and C. album are the main species throughout the world.However, the high frequency

of related species in relation to a country is alsoapparent: A. albus L. e A. lividus L. in

Italy; A. blitoides S. Watson in Israel and Portugal; A.deflexus L. in Portugal and Italy;

A. hybridus L. in France; C. opulifolium Schrader inPortugal; C. polyspermum L. in

Israel and Italy; C. murale L. in Morocco. Among thePolygonaceae, the main species

are Polygonum aviculare, Fallopia convolvulus (L.) A. Loeve(syn. P. convolvulus L.) and

P. persicaria L. (Table1).

Solanum nigrum (black nightshade) and related species arenotorious and often

troublesome weeds of agriculture and horticulture in mostparts of the world (Holm et al.,

1977; Edmonds and Chweya, 1997): they occur in at least 73countries where they are

associated with 37 major crops, including tomato (Rogersand Ogg, 1981).

Solanum nigrum L. is a key weed in the Mediterranean Area(Branthôme, 1990,

1994; Dumas, 1992; Zaragoza et al., 1994; Montemurro andTei, 1998; Viggiani et al.,

1998), North America [Alex, 1964; Ogg et al., 1981; Rogersand Ogg, 1981; Weaver et

al., 1987; McGiffen et al. (1992)], South America (Ronchiet al., 2010) and Asia (William

and Chiang, 1980). This species is characterized by a longperiod of emergence: for

example, in Central Italy fluxes of emergence are frommid-April to mid-July (Covarelli and

Peccetti, 1986). Other species very close to S. nigrum arealso troublesome for processing

tomato crops in some countries: S. sarrachoides Sendtn. andS. physalifolium Rusby in

Table 1 Distribution of key weeds and species is becomingimportant in tomatoes

Weed species Botanical family Countries

Alopecurus myosuroides Hudson Graminaceae CNE

Cynodon dactylon (L.) Pers. Graminaceae Med.

Digitaria sanguinalis (L.) Scop. Graminaceae Med.

Echinochloa crus-galli (L.) Beauv. Graminaceae Med., mostimportant in the United States

Lolium spp. Graminaceae CNE

Lolium multiflorum Lam Graminaceae very widespread inCentral-Southern IT

Paspalum paspaloides (Michx.)

Scriber Graminaceae PT

Phalaris spp. Graminaceae CNE, very widespread inCentral-Southern IT

Setaria spp. Graminaceae Med.

Sorghum halepense (L.) Pers. Graminaceae Med.

Ambrosia artemisiifolia L. Asteraceae FR, HR

Anthemis spp. Asteraceae Central IT

Cirsium arvense (L.) Scop. Asteraceae CNE, FR

Galinsoga parviflora Cav. Asteraceae CNE, PL

Matricaria chamomilla L. Asteraceae CNE

Senecio vulgaris L. Asteraceae CNE

Sonchus spp. Asteraceae CNE

Xanthium spp. Asteraceae ES, Southern IT

Capsella bursa-pastoris (L.)

Medicus Brassicaceae CNE

Coronopus squamatus (Forskal)

Ascherson Brassicaceae CNE

Raphanus raphanistrum L. Brassicaceae CNE

Sinapis arvensis L. Brassicaceae CNE

Thlaspi arvense L. Brassicaceae CNE

Fumaria officinalis L. Papaveraceae CNE, Central IT

Fallopia convolvulus (L.) Holub Polygonaceae Med.

Polygonum spp. Polygonaceae Med.

Polygonum arenastrum Boreau Polygonaceae IL

Polygonum aviculare L. Polygonaceae Med.

Polygonum persicaria L. Polygonaceae Med.


Calystegia sepium (L.) R. Br. Convolvulaceae Northern IT

Convolvulus arvensis L. Convolvulaceae MA, IL

Cuscuta campestris Yuncker Convolvulaceae ES, IL

Amaranthus spp. Amaranthaceae Med.

Amaranthus albus L. Amaranthaceae IT

Amaranthus blitoides S. Watson Amaranthaceae IL, PT

Amaranthus deflexus L. Amaranthaceae IT, PT

Amaranthus hybridus L. Amaranthaceae FR

Amaranthus lividus L. Amaranthaceae IT

Amaranthus retroflexus L. Amaranthaceae main speciesthroughout the world

Chenopodium spp. Amaranthaceae Med.

Chenopodium album L. Amaranthaceae main species throughoutthe world

Chenopodium murale L. Amaranthaceae MA

Chenopodium opulifolium Schrader Amaranthaceae PT

Chenopodium polyspermum L. Amaranthaceae IT, IL

Salsola kali L. Amaranthaceae ES

Datura stramonium L. Solanaceae ES, PT, IT, HR, MA

Solanum spp. Solanaceae Med.

Solanum americanum Mill. Solanaceae (South America)

Solanum elaeagnifolium Cav. Solanaceae (IL)

Solanum luteum Mill. Solanaceae (FR)

Solanum nigrum L. Solanaceae Med.

Solanum physalifolium Rusby Solanaceae (ES)

Solanum pythicanthum Dunal Solanaceae (North America)

Solanum sarrachoides Sendtn. Solanaceae (ES)

Solanum sisymbrifolium Lam. Solanaceae (South America)

Lamium spp. Lamiaceae CNE

Stachys annua L. Lamiaceae CNE

Euphorbia chamaesyce L. Euphorbiaceae ES

Euphorbia heterophylla L. Euphorbiaceae IL

Euphorbia maculata L. Euphorbiaceae IL

Abutilon theophrasti Medicus Malvaceae ES, Northern IT, HR

Table 1 (Continued )


Hibiscus trionum L. Malvaceae Northern IT

Malva parviflora L. Malvaceae MA

Orobanche spp. Orobanchaceae widespread in MediterraneanArea, Asia, Southern and Eastern Europe

Orobanche aegyptiaca Pers. Orobanchaceae IL

Orobanche crenata Forsk. Orobanchaceae PT

Orobanche ramosa L. Orobanchaceae ES, Southern IT

Cyperus spp. Cyperaceae ES, PT, Southern IT

Anagallis arvensis L. Primulaceae CNE

Ecballium elaterium (L.) A. Rich. Cucurbitaceae Southern IT

Equisetum spp. Equisetaceae Central IT

Phytolacca americana L. Phytolaccaceae Northern IT

Portulaca oleracea L. Portulacaceae Med.

Tribulus terrestris L. Zygophyllaceae Southern IT

Veronica spp. Veronicaceae CNE, Central IT

ISO 3166-1 alpha 2 country codes: ES, Spain; FR, France;HR, Croatia; IL, Israel; IT, Italy; MA, Morocco;

PL, Poland; PT, Portugal.

Med.: common species throughout the Mediterranean Area (Teiet al., 2003).

CNE: species frequent in early direct-sown crops and alsoin transplanted crops in Central-Northern Europe

(Tei et al., 2003).

Bold: species belonging to Amaranthus and Chenopodiumgender with high frequency in relation to the countries.

Italics: species that have increasing frequency andabundance in weed communities in field crop processing

tomato in the Mediterranean Area (Tei et al., 2003).

( ): species very close to S. nigrum that are alsotroublesome for processing tomato in some countries.

Table 1 (Continued )

Spain (Zaragoza et al., 1994), S. luteum Mill. in France(Branthôme, 1990, 1994; Dumas,

1992), S. elaeagnifolium Cav. in Israel, S. pythicanthumDunal in North America (Weaver

and Tan, 1987; Bucklew et al., 2006; Hillger et al., 2006b)and S. americanum Mill. and

S. sisymbrifolium Lam. in South America (Hernandez et al.,2002, 2007) (Table 1).

Echinochloa crus-galli is the most important grass weed inthe Mediterranean Area and

the United States (Norris et al., 2001a,b), but Digitariasanguinalis (L.) Scop., Setaria spp.,

Sorghum halepense (L.) Pers., and Cynodon dactylon (L.)Pers. are frequent too (Tei et al.,

2003). Lolium multiflorum Lam. and Phalaris spp. are verywidespread in Central-Southern

Italy (Viggiani et al., 1998) (Table 1).

Among the perennial species, besides the already mentionedC. arvense, S. halepense

(Andujar et al., 2013) and C. dactylon, Rumex spp.,Convolvulus arvensis L. and Cyperus

spp. are a key problem at the local level (Holm et al.,1977; Williams, 1982; Santos et al.,

1997; Morales-Payan et al., 2003; Gilreath and Santos,2004; Adcock et al., 2008; Alves

et al., 2013).

Among parasitic plants, Phelipanche and Orobanche spp.(broomrapes) are widespread

in Mediterranean climate areas, in Asia and in Southern andEastern Europe (Parker

and Riches, 1993; Joel et al., 2007; Hershenhorn et al.,2009), while Cuscuta campestris

Yuncker is widespread in Spain and Israel (Tei et al.,2003) (Table 1).

However, because of the selection resulting from agronomicpractices (mainly chemical

weed control methods and simplified crop rotation), severalspecies have become

more important and are causing increasing problems at thelocal level. For example, for

Mediterranean Area, Tei et al. (2003) reported thefollowing species that have increasing

frequency and abundance in weed communities in field cropprocessing tomato (Table 1):

• Poland: Galinsoga parviflora;

• France: Ambrosia artemisiifolia L., Cirsium arvense and

triazine-resistant biotypes of Amaranthus hybridus;

• Spain: Datura stramonium L., Abutilon theophrastiMedicus, Xanthium strumarium L., Salsola kali L.,Euphorbia chamaesyce L., Cynodon dactylon, Cyperus spp.,Sorghum halepense, Orobanche ramosa L.;

• Portugal: Datura stramonium, C. dactylon, Paspalumpaspaloides (Michx) Scriber, Cyperus spp., Orobanchecrenata Forssk.;

• Northern Italy: Abutilon theophrasti, Hibiscus trionumL., Phytolacca americana L., Calystegia sepium (L.) R.Br.;

• Central Italy: Anthemis spp., Equisetum spp., Fumariaspp., Veronica spp.;

• Southern Italy: Cyperus spp., Ecballium elaterium (L.) A.Rich., Tribulus terrestris L., Xanthium spinosum L., O.ramosa;

• Croatia: A. theophrasti, A. artemisiifolia and D.stramonium;

• Morocco: C. arvensis, D. stramonium, Malva parviflora L.,C. dactylon, Orobanche spp.

• Israel: triazine-resistant biotypes of Amaranthusblitoides S. Watson, C. arvensis, Euphorbia heterophyllaL., E. maculata L., Polygonum arenastrum Boreau, O.aegyptiaca Pers [syn. Phelipanche aegyptiaca (Pers.)Pomel].

3 The effect of weed–crop interference

Weeds are damaging to tomato crops for several reasons.Weed competition for resources,

such as light, water and mineral nutrients, can cause yieldand produce quality reductions

(i.e. a decrease of grade in size, colour and shape). Thelevel of damage depends on

the composition and density of the weed community and theduration of the period of

interference (Friesen, 1979; Monaco et al., 1981; Weaverand Tan, 1987; Bhowmik and

Reddy, 1988a; Perez and Masiunas, 1990; Qasem, 1992a,b,1993; McGiffen et al., 1992,

1994; Patrap et al., 1997; Santos et al, 1997; Viggiani andDellacecca, 1998; Norris et al.,

2001a; Morale-Payan et al., 2003; Nascente et al., 2004;Bucklew et al., 2006; Hernandez

et al., 2002, 2007).

Tall (e.g. C. album, Xanthium italicum Moretti) or trailing(e.g. Convolvulus arvensis,

C. sepium) weeds can make the mechanical harvesting ofprocessing tomato impossible;

more generally, weeds can increase the cost of cropproduction due to an increase in

labour and harvesting costs.

Parasitic weeds can directly serve as vectors of tomatoplant pathogens, reservoir

alternative hosts for pathogens and vectors and obligatealternative hosts for some

pathogens (Wisler and Norris, 2005). For example, severalCompositae, Lamium purpureum

L., Malva sylvestris L., Mercurialis annua L., P. oleracea,Solanum spp. and S. media host

Cucumber Mosaic Virus (Tomlison and Carter, 1971); Cirsiumspp., P. oleracea and Solanum

spp. host Potato Virus Y; Plantago spp. and Solanum spp.host Tobacco Mosaic Virus; A.

retroflexus, D. stramonium, P. oleracea, Stellaria media(L.) Vill. and some Compositae

host Tomato Spotted Wilt Virus (Groves et al., 2002);several species of the families

Amaranthaceae, Asclepiadaceae, Chenopodiaceae,Convolvulaceae, Euphorbiaceae,

Solanaceae, Compositae, Malvaceae, Plantaginaceae,Leguminosae and Umbelliferae

can harbour Tomato yellow leaf curl virus as alternativehosts (Bedford et al., 1998; Jorda

et al., 2001; García-Andrés et al., 2006; Gal-On et al.,2009; Papayiannis et al., 2011).

Corynebacterium michiganense pv. Michiganense (tomatocanker) is hosted by S. nigrum,

Xanthomonas campestris pv. vesicatoria (bacterial spot oftomato) by D. stramonium and

S. nigrum, and Pseudomonas syringae pv. Tomato (bacterialspeck of tomato) by Brassica

spp., Lamium amplexicaule L. and S. media (McCarter et al.,1983). As a consequence,

besides the use of tolerant and resistant cultivars whenthey exist, an IPM programme

should include an effective weed management programme inorder to reduce the risk of

transmission of those pathogens to the crop.

Weeds can reduce the value of land. Heavily infested landswith perennial (e.g. Cyperus

spp.) and/or parasitic weeds (Phelipanche and Orobanchespp.) fetch less price or are

unusable for growing tomato crops (Cirujeda et al., 2012;Hershenhorn et al., 1998b; Abu

Irmaileh and Labrada, 2008).

4 Integrated weed management (IWM)

The challenges for weed research at the start of the newmillennium were pinpointed by

Kropff and Walter (2000), who wrote, ‘Increasing concernabout the environmental effects

of herbicides, the development of herbicide-resistant weedsand the necessity to reduce

the cost of inputs have resulted in a greater pressure onfarmers to reduce the use of

herbicides. … The challenge today is to develop a trulyintegrated crop management

system in which preventive measures are taken first,followed by precision control.’

Particularly in Western Europe, and to a certain extent inthe United States, Canada

and other countries (e.g. Sweden, Denmark), these concernshave begun to translate

into changes in public policy, research priorities andmarket opportunities that favour the

development of low-external-input and organic farmingsystems (Liebman et al., 2003)

where the scope of IWM should be expanded with the aim ofmaximizing profit margins,

safeguarding natural resources and minimizing the negativeimpact of weed control

practices on the environment (Sanyal et al., 2008).

IWM can be regarded as a ‘tool box’ where, in a givenagroecosystem, the different

tools such as agronomic practices and direct weed controlmethods should be chosen and

harmonized in the context of both short- and long-termstrategies to achieve the following

main goals:

• reduction of weed soil seed bank;

• prevention of weed seed production and/or dissemination;

• reduction of the density of weeds emerging in the crops;

• increase of crop competitive ability against weeds (ordecrease of relative weed competitive ability) and

• control of emerged weeds by a ‘reduced’ use of herbicides.

Thus, IWM needs the scientific knowledge of both weedbiology and ecology (Bhowmik,

1997; Mortensen et al., 2000), agronomy (Munier-Jolain etal., 2005) and weed control

methods strongly related to precision technology andstrategy (e.g. in-row mechanical

control, localized application of herbicides, optimizationof herbicide rates, use of threshold

density …) for bringing about an environmentally soundagroecosystem management

(Bastiaans et al., 2008).

All these aspects have been taken into consideration in thedefinition of IWM systems

for tomatoes, mainly field crop processing tomatoes, asalready reviewed by different

authors (Branthôme, 1990, 1994; Zaragoza et al., 1994;Montemurro and Tei, 1998; Tei

et al., 1999, 2003; Zaragoza, 2003; Montemurro andPreziosa, 2000; Hillger et al., 2006b;

Ronchi et al., 2010; Lanini et al., 2014).

5 Preventative measures and cultural control: croprotation and cover crops

Preventive measures have the main aim of avoidingaccidental introduction and dispersion

of weed seeds and propagules: they include the use ofweed-free planting material,

cleaning of cultivation and harvester machineries,filtering of irrigation water and managing

the non-cultivated nearby areas (e.g. field margins,drainage ditches) (Zaragoza, 2003).

Many researchers have demonstrated that rotating crops withdifferent morphology,

eco-physiology, life cycle and associated culturalpractices is the foundation for an IWM

in conventional, low-external-input and organic croppingsystems (Poudel et al., 1998;

Anderson, 2005; Hiltbrunner et al., 2008; Eyre et al.,2011) because crop rotation

• reduces specific tomato pathogens and pests and ‘soilsickness’ (Dumas, 1992);

• prevents the proliferation and dominance of particularweed species adapted to specific cultural situations (e.g.Solanum nigrum, perennial and parasitic weed species)(Vergniaud et al., 1984);

• maintains the diversity of the weed community, and so aless competitive and easierto-manage flora (Liebman andDyck, 1993);

• allows an easier chemical weed control of some key weedsof tomato crops (e.g. Solanum nigrum) in the other cropsof the crop sequence (Montemurro and Preziosa, 2000).

Frequently, tomato crop is the ‘weak ring’ of the cropsequence ‘chain’ particularly in

organic cropping systems where weed control is moredifficult.

Graziani et al. (2012) studied the effect of severalrotations on soil seedbank density

and composition in both organic and conventional low-inputfarming systems in

Mediterranean climates and showed that the significantincrease of weed soil seedbank

recorded in the organic farming system was mainly due to anincrease of summer weed

species (i.e. P. oleracea, A. retroflexus and C. album) notwell controlled in vegetable

summer crops such as processing tomato and musk melon.Clark et al. (1998) showed

that in conventional and alternative (i.e. low-input andorganic) tomato and corn systems

in North California (USA), weed abundance was negativelycorrelated with tomato and

corn yields and appeared to partially account for loweryields in alternative systems than

in conventional ones. In Southern California vegetablecropping systems, infestations of

Cyperus rotundus L. and C. esculentus L. were managed byintroducing fallow in the crop

sequence (Wang et al., 2008).

The use of cover crops in the crop sequence may involveallelopathic interactions

between the vegetables and other crops or weeds (Bhowmikand Inderjit, 2003; John

et al., 2010). Several authors (e.g. Müller-Schärer andPotter, 1991; Masiunas, 1998; Price

and Norsworthy, 2013) suggested the use of cover crops(generally grasses, legumes and/

or crucifers) to either improve weed management and/orincrease soil fertility, or reduce

the risk of soil erosion by wind and water in vegetablecropping systems.

In vegetable crops, cover crops may be used as ‘greenmanure’ (e.g. Al-Khatib et al.,

1997), ‘dead mulching’, leaving on soil their dead residues(Kruidhof et al., 2011) and

‘living mulching’ (i.e. intercropping) (Theunissen, 1997;Baumann et al., 2000; Brainard and

Bellinder, 2004; Gibson et al., 2011). Cover crops need tobe managed carefully in order

to improve weed management and increase environmentalbenefits, and to minimize the

potential negative effects for crop production (denHollander et al., 2007).

Smeda and Weller (1996) reported rye (Secale cereale L.) asa valuable winter cover

crop producing plant mulch of considerable allelopathicactivity and which is effective in

reducing weed infestation in transplant tomato. Campigliaet al. (2010a,b) reported that

hairy vetch (Vicia villosa Roth.) mulches, in sole crop orin mixture with oat (Avena sativa L.),

combined with reduced mechanical or chemical weed control,could be a feasible strategy

to control weeds and to increase yields in tomato.Campiglia et al. (2015) compared five

soil managements [three cover crop species: hairy vetch,phacelia (Phacelia tanacetifolia

Benth.) and white mustard (Sinapis alba L.); winter fallowmulched with barley straw before

tomato transplanting; conventionally tilled soil], twonitrogen fertilization levels (0 and

100 kg N ha –1 ) and two weed management levels (weed-freeand weedy) on tomato;

cover crop residues were arranged in strips on the soilsurface and then used as beds for

transplanting the tomato seedlings in paired rows; rotaryhoeing was performed in the

bare strips between paired tomato rows. Results confirmedthat hairy vetch used as a

cover crop and dead mulch was the most suppressive specieswith the highest production

of residues, while phacelia and mustard were not suitablefor controlling weeds; the mulch

strips caused variations in the composition of weedspecies, a species that was mainly

made up of perennial ruderal weeds, while in tilled soil,the weed flora was dominated

by annual photoblastic weeds. Galvão et al. (2013) found inBrazil that hairy vetch and

radish (Raphanus sativus L.) were the most indicatedpreceding cover crops for tomato

cultivation.

A number of studies have examined legume cover crop use inreduced tillage. Results

indicated that these covers performed best as a mixturewith a cereal grain rather than in

a monoculture (Brennan et al., 2009; Tosti et al., 2012).Research in reduced-tillage tomato

production found higher yields and successful weed controleither alone or in mixture

(Abdul-Baki et al., 1996; Creamer et al. 1996). Morerecently, legume covers were reported

to provide early-season weed suppression, but they requiredsubsequent herbicide

applications to maintain season-long weed suppression intomato (Saini et al., 2007).

Phelipanche and Orobanche parasitic weed species can bemanaged by inserting

‘trap crops’ (Joel et al., 1995). The use of trap cropsoffers the advantage of stimulating

Orobanche and Phelipanche germination without beingparasitized (the broomrape does

not attach the roots or develop tubercles) and nothampering the growth and yield of

crops (Dhanapal et al., 1996; Rubiales et al., 2009a). Soilseed bank of broomrape was

reduced by planting trap crops like peas (Pisum sativumL.), sesame (Sesamum indicum

L.), brown Indianhemp (syn. kenaf, Hibiscus cannabinus L.),mungbean [Vigna radiata (L.)

R. Wilczek], garlic (Allium sativum L.), pepper (Capsicumannuum L.) and common flax

(Linum usitatissimum L.) in rotation (Linke and Saxena,1991; Linke et al., 1993; Hershenhorn

et al., 1996). In a single season, the use of these cropsstimulated the germination of soil

broomrape seed bank by 15–35% (Linke and Saxena, 1991;Schnell et al., 1994). Sesame,

brown Indianhemp, common flax and black-eyed pea (Vignaunguiculata L.) decreased

broomrape biomass by about 86, 85, 75 and 74%,respectively. Reducing broomrape

biomass caused increases in tomato yield; meanwhile,sesame, brown Indianhemp,

Egyptian clover (Trifolium alexandrinum L.) and mungbeanincreased the total biomass

of tomato by about 71, 68, 66 and 63%, respectively (Babaeiet al., 2010). Kleifeld et al.

(1994a) observed that growing flax in two successive winterseasons or one summer

cropping with mungbean reduced the early infestation ofPhelipanche aegyptiaca and

significantly increased tomato vigour and production.

6 Cultural control: stale seedbed preparation, cultivarselection, planting, irrigation and fertilization

Pre-plant seedbed preparation and other forms ofdisturbance confined to the top 10 cm

of soil (i.e. superficial soil disturbances) can increaseweed seedling emergence compared

with undisturbed soil (Egley, 1989; Peruzzi et al., 2011).Minimizing soil disturbance is

aimed at stimulating the first flush of emerging weedsbefore crop transplanting or crop

sowing (Schutte et al., 2014), depleting weed seedbanks andthus reducing subsequent

weed flushes (Colquhoun and Bellinder, 1996).

Then the emerged weeds can be removed by shallowcultivation with flexible tine, by

other physical weed control methods (i.e. flaming, steaming…) or by pre-sowing or pre

planting the application of total herbicides (e.g.glyphosate or glufosinate-ammonium).

Stale seedbed preparation is widely used as a control ofthe early-emerging weeds,

including the first-emergence fluxes of S. nigrum in tomatocrops, in both conventional

and organic cropping systems (Branthôme, 1994).

Tomato cultivars should be selected not only for highyield, quality characteristics and

disease resistance, but also for morphological andphysiological characteristics (e.g. root

development, initial rapid growth, dense and large leafcanopy, allelopathic activity …)

that determine a good competitive advantage against weeds(Ngouajio et al., 2001;

Lammerts van Bueren et al., 2011). Breeding tomatocultivars for broomrape resistance is

deemed effective and an environmentally friendly managementstrategy for coping with

this parasitic weed (El-Halmouch et al., 2006; Dor et al.,2010; Tokasi et al., 2014).

Other cultural control techniques include planting method,planting pattern, row spacing

and crop density. Tomato crop transplanting instead ofdirect seeding could increase the

crop competitive ability against weeds and an easieradoption of weed control direct

measures (Weaver, 1984). With high infestation of S.nigrum, the combination of stale

seedbed preparation and crop transplanting allows largertomato plants than the weeds

from the very beginning of the crop cycle and, as aconsequence, a higher herbicide

selectivity and efficacy that are dramatically dependent oncrop and weed growth stages

(Onofri et al., 1995; Frost and Barnes, 2003).

Increasing crop density and reducing row spacing canincrease the competitive ability of

crops against weeds (Fischer and Miles, 1973) with aconsequent decrease of weed seed

production (Norris et al., 2001b) and increased growth andyield of tomato (Norris et al.,

2001a). However, Norris et al. (2001a,b), in their researchon competition between tomato

and Echinochloa crus-galli L. Beauv (barnyardgrass), foundthat although some effects

of increasing tomato density on barnyardgrass growth wereobserved, manipulation of

crop density would appear to be useful as a managementstrategy only if barnyardgrass

densities were very low; because of the high fecundity ofbarnyardgrass, results suggested

that stopping seed production is the best long-termmanagement strategy against the

weed.

Localized irrigation (i.e. surface and sub-surface drip

irrigation systems) instead of furrow

and sprinkler irrigation could limit surface soil wettingand thus inhibit germination and

growth of weeds (Phene et al., 1987; Grattan et al., 1988).Sutton et al. (2006) recorded

10 to 14 times greater weed biomass at tomato harvest onbeds in the furrow systems

compared to that on the sub-surface drip irrigationsystems, thus indicating that weed

competition was reduced in conservation tillage systemswithout herbicide applications.

Valerio et al. (2013), in a field experiment in SouthernItaly, found that the relative effect

of weed biomass on crop loss appeared to increase underdrought than under irrigated

conditions. This confirms the importance of crop watermanagement for IWM in tomato:

if drought conditions increase with climate change, theremay be a greater need for a

complete and thorough weed control for this productionsystem.

The effect of fertilizer management on weed emergence andcrop–weed competition

varies with weed species and N rates (Sweeney et al., 2008;Blackshaw and Brandt, 2008);

however, most species respond positively to increased Navailability, leading to potentially

greater crop losses through competition (Blackshaw et al.,2003). In this context, placing

fertilizer in the proximity of a crop row benefits cropsmore than weeds, thus reducing

weed competition (DiTomaso, 1995).

7 Decision making: weed competition thresholds

A number of studies on weed–crop competition have beenaimed at defining the

quantitative threshold to be used in the decision-makingprocess in the IWM. The

thresholds take into consideration two kinds of variables(Zimdahl, 2004):

• weed density, that is, the minimum number of weed plantsper m 2 above, which need direct weed control measures inorder to prevent yield losses and the

• duration of competition, that is, the critical period ofweed competition (CPWC) defined (Zimdahl, 1988) as a spanof time between the period after crop seeding, emergenceor transplanting when weed competition does not reduce cropyield [i.e. duration of tolerated competition (DTC)] andthe period after which weed competition will no longerreduce crop yield (i.e. minimum weed-free period, WFP).

The quantitative relationship between weed density andtomato yield has been well

researched (see, for example, Zimdahl, 2004; Ronchi et al.,2010), but only a few studies

have determined weed density thresholds, and where done,they have mainly focused

on the effect of a single key weed. The threshold densityof S. nigrum in Italy and France

was about one plant per linear metre in transplantedprocessing tomato (Maillet and

Abdel Fatah, 1983; Damato and Montemurro, 1986) and closeto zero in seeded crops

(Caussanel et al., 1989, 1990; Jacquard and Abdel Fatah,1988).

The practical use of a single key weed density thresholds,although interesting, is of

limited practical interest for IWM because weed communitiesare species-rich and the

availability of reliable decision-support systems (DSS),

where weed density thresholds

could be efficiently used, is quite low, particularly incase of multi-species weed infestation

(Sattin and Berti, 2003).

On the contrary, the determination of the CPWC is deemed tobe particularly interesting

both in conventional and organic cropping systems tominimize yield losses for many crops

(Zimdahl, 1988). The knowledge of the DCT allows the choiceof the best timing of weed

control treatment, both chemical (e.g. post-emergencetreatments), physical (e.g. duration

of biodegradable mulching) or mechanical during the firstpart of the crop cycle to prevent

the effect of competition due to early-emerging weeds; theknowledge of ‘minimum weed

free period’ (WFP) allows mainly the choice of a herbicidewith an adequate residual effect

in relation to weed emergence, crop cycle and herbicideselectivity to the succeeding

crop.

In the experiments that evaluated the effect of time ofweed emergence and time

of removal on crop yield, the CPWC has been determined byfollowing three different

approaches (Sattin and Berti, 2003): classical, functionaland economic. In the classical

approach (Zimdahl, 1988), the critical period is calculatedby mean separation, so it is

possible to identify a period within which no statisticallydetectable yield losses occur. The

functional approach (e.g. Van Acker et al., 1993; Knezevicet al., 2002) is characterized

by the use of regression analysis. Therefore, it isnecessary to fix a ‘sustainable’ yield loss

threshold in order to determine a critical period (e.g.2.5, 5 or 10%). Finally, the economic

approach (Dunan et al., 1995) defines the economic criticalperiod as the time interval

when the marginal income of weed control is higher than thecost of control.

The effect of the duration of weed competition onprocessing tomato has been well

studied. Results showed that the CPWC (i.e. the timebetween DCT and WFP) in field

seeded crops was from about 30 to 60 days after emergence(Duranti and Carone, 1983;

Weaver and Tan, 1983; Marana et al., 1983; Weaver, 1984),while in transplanted crops it

was from about 24 to 40 days after planting (Labrada andSantos, 1977; Friesen, 1979;

Weaver and Tan, 1983; Lugo et al., 1988; Bhowmik and Reddy,1988b; Perez and Masiunas,

1990; Montemurro et al., 1991; Qasem, 1992b).

Nascente et al. (2004) found a CPWC from 33 and 76 DaysAfter Transplanting (DAT)

in processing tomato grown in a tropical environment (i.e.Brazil). Morales-Payan et al.

(2003) found that with densities of 25–50 Cyperusesculentus (yellow nutsedges) per m 2 ,

the suppression of this weed for the first 8 weeks aftertransplanting would be necessary

to prevent > 5% total marketable yield loss (i.e. DCTthreshold) of plastic mulched fresh

market tomato in Florida.

In a research in processing tomato in Brazil with aninfestation of Solanum americanum,

Hernandez et al. (2007) found that to prevent a >5% totalmarketable yield loss, the CPWC

was from 25 to 46 DAT. In transplanted plasticulture tomatoinfested by Eastern black

nightshade (Solanum ptycanthum), Bucklew et al. (2006)found a CPWC from 28 and 50

DAT to maintain yield losses less than 20%.

Although experimental results are not easily comparable dueto differences in the

above-mentioned approaches, pedoclimatic conditions andweed flora, Berti et al. (2008)

found that the relationship between the time of weedemergence and removal appeared

to depend more on crop characteristics (growth ratesmainly) than on the composition of

the weed infestation. So, in tomato, DCT seems to lastthroughout the exponential growth

phase, while WFP starts at about half of the linear growthphase; as a consequence, the

CPWC corresponds to the phases during which tomato cropshows the highest crop

growth rates.

Since direct-seeded tomato crops show slow emergence andinitial growth and as a

consequence they are very sensitive to weed competition,transplanting increases crop

competitive ability in the first part of the growth cycleand allows a reduction of WFP and

CPWC (e.g. Weaver et al., 1987).

However, since both weed density and duration competitionthresholds are commonly

determined on a ‘single-crop-cycle’ basis, uncontrolledweeds (although below the

thresholds) may spread their seeds, increasing the soilseed bank (Dawson, 1986) and thus

increasing the weed infestation in the crop rotation(Gallandt, 2006) and the herbicide

rates in subsequent years (Taylor and Hartzler, 2000).

Norris (1999) proposed a ‘no-seed-threshold’ (NST) approachin IWM that will not allow

the weed community to produce seed: this approach is basedon intense weed control in

the initial years, during which the seed bank would bedepleted rather quickly, followed

by lower weed control inputs in subsequent years.

8 Direct weed control methods: mulches, solarization,thermal and mechanical methods and hand weeding

In organic crop management, the use of herbicides isprohibited, and therefore, besides

cultural measures, physical weed control methods play acrucial role both in ensuring

an effective direct weed control and in reducing the labourcost of hand weeding.

Considerable improvements have been made in the last twodecades in non-chemical

weed management in vegetables (Parish, 1990; Rasmussen andAscard, 1995; Bond and

Grundy, 2001; Upadhyaya and Blackshaw, 2007). Some of thesemethods are currently

used (e.g. mulching, solarization, flaming and steaming),some need further research and

technology development (e.g. microwave, freezing) and somedo not seem to be used

presently (e.g. electrocuting and lasers).

8.1 Non-living mulches

The non-living mulches for weed control can be classifiedinto two main groups:

• particle mulches with natural materials: leaves, strawand hay, sawdust, shredded and chipped bark, grassclipping, etc.;

• sheeted mulches: black and coloured polyethylene sheets,needle-punched fabrics, paper mulches, biodegradablefilms.

Their efficacy for weed control and for the improvement ofsome physical, chemical and

biological soil characteristics has been extensivelystudied in vegetable crops (Grundy

and Bond, 2007; Coolong, 2012), including in tomato crops(Moreno and Moreno, 2008;

Mukherjee et al., 2010; Campiglia et al., 2015).

Organic mulches are used mainly in organic croppingsystems: their efficacy depends

on the mulch layer height (Teasdale and Mohler, 2000),while their economic convenience

depends on the material origin (Runham and Town, 1995). Oneof the most commonly

used organic mulches in organic tomato is cereal straw,which is cheap, as it is a by-product

of plant production; straw mulch showed similar tomatoyield when compared to plastic

mulch and a higher tomato yield than that obtained in thebare soil (Radics and Bognar,

2004; Radics et al., 2006; Anzalone et al., 2010).

Among the plastic sheets, black low-density polyethylene(LDPE) is the most widely

used mulch for weed control in both processing and fresh

market tomato due to its high

efficacy against weeds, a relatively good soil warming andlow cost. Wavelength-selective

plastic films (or infrared-transmitting, IRT) that werefrequently coloured (e.g. brown, blue,

blue-green, white-on-black, red, yellow) were developed toafford the weed control of

black mulch and increase soil temperature between black andclear mulch (Lament, 1993;

Ngouajio and Ernest, 2004; Coolong, 2012).

In the last decade, starch-based biodegradable films weredeveloped and successfully

used in field tomato crops (Martin-Closas et al., 2008;Miles et al., 2012): a mulching

action should be ensured for a sufficient number of weeksto cover the CPWC so that

they could be incorporated into the soil at the end of thecrop season. Their mulching

action and effectiveness can be affected by composition andthickness as well as exposure

to light, temperature and moisture (Kyrikou andBriassoulis, 2007; Moreno and Moreno,

2008; Waterer, 2010).

Also paper mulches can be used for weed control in freshmarket (Radics and Bognár,

2004) and processing tomato (Cirujeda et al., 2012). Papermulches have been developed

and experimentally evaluated alone (Runham et al., 2000;Radics et al., 2006), in combination

with biodegradable polymers (Weber, 2003), combined withstarch (Zhang et al., 2008),

or coated with vegetable oil treatment for slowing theirdegradation in the field (Shogren

and Hochmuth, 2004; Grundy and Bond, 2007). Despite beingbiodegradable and leading

to acceptable weed control and yield in most of the cases,paper mulch has not become

a commercial alternative to PE due to heavier reels, slowermulching speed and the need

for careful installation to avoid tears (Cirujeda et al.,2012).

A specific problem with mulching is posed by Cyperus spp.because LDPE mulches are

punctured by these weeds and therefore control only a smallproportion of these plants

(Webster, 2005); moreover, the patch size of the purplenutsedge underground increased

under plastic almost twice as much compared to thenon-mulched control, and therefore,

LDPE mulching may even aggravate the problem (Webster,2005). It is for this reason that

several researches were carried out to evaluate theeffectiveness of the combination of

plastic mulching and chemical weed control for managingnutsedge infestation (Gilreath

and Santos, 2004; Adcock et al., 2008; Culpepper et al.,2009; Dittmar et al., 2012a; Alves

et al., 2013; McAvoy and Freeman, 2013).

Also, paper mulch showed good efficacy in controlling C.rotundus (Cirujeda et al., 2012):

paper mulch does not prevent weed emergence but showresistance to the puncture,

and therefore, purple nutsedge plants develop yellow leaveswith reduced growth. Paper

mulch without special additives can satisfactorily controlC. rotundus in processing tomato,

provided the climate is conducive for maintaining the paperdry for most of the time;

persistent rainfall or sprinkler irrigation can soften thepaper and allow purple nutsedge

to perforate it; paper mulch coated with vegetable oilsseems to show more resistance in

rainy conditions (Shogren and Hochmuth, 2004). Paperdegrades quickly along the edges

where it was covered by soil (Weber, 2003).

8.2 Solarization

Solarization is a soil disinfection technique that usespassive solar heating based on covering

moistened soil with a transparent plastic film for a periodof four to eight weeks during the

hot season. Favourable climatic conditions can ensure aneffective control of soil-borne

pathogens, nematodes and weeds (Elmore, 1989). Weed speciesdiffer in sensitivity to

solarization (El-Keblawy and A-Hamadi, 2009): an exhaustivelist on the response of weeds

to solarization has been provided by Cohen and Rubin(2007). Although solarization was

found to be effective in both field and glasshouse, itsapplication is commonly restricted

to greenhouse tomato crops (Candido et al., 2008; Lombardoet al., 2012).

Soil solarization is particularly effective in parasiticweed control. In a research carried

out in Italy on greenhouse tomato infested by branchedbroomrape (Orobanche ramosa),

Mauromicale et al. (2005) found that in solarized soil nobroomrape shoots emerged, and

neither haustoria nor underground tubercles of the parasitewere found on tomato roots;

the treatment killed about 95% of buried viable seed, andinduced secondary dormancy

in the remaining 5%.

8.3 Thermal weed control

Thermal weed control includes flaming, infrared radiation,steaming, using hot water

and electrocution (Ascard and Van der Weide, 2011). Flameweeding can be considered

the most widely used thermal weed control methods, mainlyused in organic vegetable

farming systems (Ascard et al., 2007). In vegetable cropsflaming may be applied: (a) in

pre-sowing or pre-transplanting after a stale seedbedpreparation (Cloutier et al., 2007);

(b) in pre-emergence, for non-selective weed control priorto slow-emerging crops such

as carrot, onion and parsley (Ascard, 1995); (c) inpost-emergence, for selective intra

row weed control in some taller and heat-tolerant crops(e.g. onion, sweet corn, tomato)

(e.g. Ascard and Van der Weide, 2011) and as inter-rowtreatment with or without

shielding to protect crops (e.g. cabbages, artichoke) (e.g.Raffaelli et al., 2004; Ascard

et al., 2007).

Wszelaki et al. (2007) conducted a research in processingtomato where flaming

was applied 10–14 weeks after transplanting with theburners were set at a 60° angle

from horizontal, 10 cm above the crop canopy at varioustractor speeds, flaming times

(morning, afternoon) and bed types (raised beds, flatground). Flaming damaged the

tomato, but by 15–20 days after flaming (DAF), all plantshad recovered. Flaming gave

a weed control up to 80% at 50 DAF. Grasses (e.g.Echinochloa crus-galli ) and succulent

(e.g. Portulaca oleracea) weeds were harder to control thanbroad leafed weeds. Flaming

reduced blossom-end rot incidence in tomato. Yields in bothcrops were greater in the

slower speed treatments (4 km/h) than in the weedy control.Flaming compared favourably

with control attainable with herbicides, but control wasmore variable and sensitive to

environmental conditions than generally expected ofherbicides.

8.4 Mechanical weed control

During previous decades, mechanical weed control methodshave been substantially

improved for application in row crops (Cloutier et al.,2007; Van der Weide et al., 2008;

Van der Weide and Bleeker, 2011). Mechanical methods can begrouped in two main

categories: inter- and intra-row cultivation.

Inter-row cultivation can be performed by hoeing,split-hoeing, brush weeders, rolling

cultivators, disc cultivators, etc. Guidance systems canassist operators to control the

weeds as close as possible to the crop rows in order toreduce the untilled strip and the

need for intra-row weed control by mechanical and/or handweeding. All these methods

show high efficacy against the weeds in the inter-row ofcrops, even at late growth

stages and high crop selectivity. Inter-row cultivation iswidely used in organic farming

systems, but a combination of this with chemical in-rowtreatments (i.e. band spraying)

is also suggested in conventional and low-input farmingsystems in order to reduce the

application of herbicides (Pannacci and Tei, 2014).

Intra-row cultivation can be performed by finger weeders,torsion weeders, weed

blower, hoes and harrows. The removal of weeds along therow centreline is a challenge

in the process of weed control in row crops becauseintra-row weeds, if not adequately

controlled, cause major problems for organic growers and sothey need additional, very

expensive, hand weeding. Intra-row cultivations are capableof removing weeds in the row

centreline, but weeds need to be small (2nd true leaf orsmaller) and the crop must be

firmly rooted (Perez-Ruiz et al., 2014).

Despite promising results from research experiments,mechanical weed control

methods show some limitations (Melander et al., 2015): someweeds normally survive the

treatment; skilful and experienced operators are needed andit is so difficult to replace

them; incorrect settings of the tools and poor timing ofapplication can easily result in

weed control failures and significant crop injury; workingrates are generally low due to

slow driving speeds and narrow implement widths. All these

limitations have motivated

researchers and industry to modernize physical weed controlmethods by equipping

tools with intelligent systems for automatic (robotic)intra-row ‘close-to-plant’ (CTP) weed

control systems (Slaughter et al., 2008; Norremark et al.,2009; Gobor et al., 2013; Perez

Ruiz et al., 2012, 2014; Melander et al., 2015).

8.5 Hand weeding

In organic vegetable farming systems, additional handweeding is often necessary to

ensure an effective weed control in row centreline incombination with cultural and non

chemical weed control measures.

Van der Weide et al. (2008) reported that in theNetherlands 45 h ha –1 were required

on average for manual weeding in transplanted vegetablesand more than 175 h ha –1 in

direct-seeded onions, while in Italy, the labour inputvaries from 24 h ha –1 for transplanted

lettuce to 162 h ha –1 for sown fennel; Melander andRasmussen (2001) have shown that

50–350 h ha –1 were required in leek and bulb onion cropsgrown in Denmark; some

authors (Smith et al., 2004; Tourte et al., 2004, 2009;Tourte and Smith, 2010) reported

that in California organic broccoli required 53 h ha –1and lettuce 40 h ha –1 on average; in

carrots, a hand-weeding input of 100–500 h ha –1 by using‘weed beds’ for 8–12 persons

is needed (Tei et al., 2002); Lichtenhahn et al. (2005)reported a labour time of 120–300

h ha –1 for celery, 100–200 h ha –1 for spinach and60–100 h ha –1 for French beans, the

lower limit in open-field cultivation and the upper limitin tunnel cultivation.

In transplanted processing tomato, Perez-Ruiz et al. (2014)reported an average need

of 24 h ha –1 of hand hoeing, while in rain-fed freshtomato, Fontanelli et al. (2013) found a

labour demand for hand weeding of about 10 h ha –1 incombination with biodegradable

mulching or mechanical–thermal treatments.

Finally, some studies were conducted to develop integratedweed control strategies

on the basis of the integration of different physical weedcontrol methods. For example,

Fontanelli et al. (2013) carried out field experiments inrain-fed fresh market tomato to

determine the effects of the following three differentstrategies:

1 mechanical–thermal: stale seedbed technique performed byrolling harrowing and flaming + post-transplantingcultivation by intra-row precision hoe and inter-rowtorsion weeder + hand weeding;

2 mechanical–thermal-straw: stale seedbed technique (asmentioned above) + wheat straw mulching + inter-mulchingcultivation + inter-mulch cultivation;

3 biodegradable plastic mulch (check): biodegradableplastic mulch + inter-mulch cultivation + hand weeding.

Results showed that all the three strategies controlledweeds effectively; however, tomato

yield was 35% higher for strategies that included mulching(both biodegradable film and

straw) due to a better crop water management in thesoil–plant system.

9 Chemical weed control

Chemical weed control is the most important and widespreadweed control method in

tomato, thanks to its higher efficacy and lower cost thanother control options. All over

the world (excluding Africa and Oceania, because ofunavailability of reliable data), the

treated tomato crop area is about 2.1 M ha (Tei andPannacci, 2016). However, because

of the potential negative side effects of herbicides onfood safety, public health and the

environment, the evolution of herbicide-resistant weeds(Powles and Yu, 2010; Heap,

2015) and the reduction of the diversity of weedpopulations (Grundy et al., 2011), the use

of chemical weed control led to public and scientificconcerns and as a consequence to

the development of low-external input and organic farmingsystems (Liebman et al., 2003)

for minimizing or avoiding the use of chemical activeingredients.

Herbicides authorized for use in tomato crops allow aneffective weed control in different

application timings in both direct-seeded and transplantedcrops, although the availability

of authorized active ingredients varies from country tocountry (Tei et al., 2003; Ronchi and

da Silva, 2010; Lanini et al., 2014; Freeman et al., 2015).

In general, the approved herbicides for use are few andsometimes technically obsolete

due to little interest from the pesticide industry ininvesting in R&D and registering the

herbicides to be used in ‘minor crops’ like tomatoes

(Fennimore and Doohan, 2008).

This leads to a situation where the repeated and frequentuse of a few herbicides causes

an increase in the frequency and abundance ofnon-controlled troublesome weed species

(e.g. S. nigrum) and the risk of the evolution of herbicideresistance.

This situation has worsened in Europe by the withdrawal oflarge numbers of active

ingredients under the Pesticide Authorisation Directive91/414/ECC aimed at facilitating

trade through harmonized regulation, improving safetystandards for consumers and

operators and decreasing environmental contamination. Forexample, metribuzin, a key

herbicide in tomato weed management, is in the list ofsubstances that may be eliminated

in 2017 as potential endocrine disruptors (Hillocks, 2012).Recently, Hesammi (2013)

showed the utility of metribuzin in an IWM approach inorder to increase weed control in

tomato crop reducing environmental pollution.

Similarly, the loss of methyl bromide and the high pricesand low efficacy against weeds

of alternative fumigants (chloropicrin and1,3-dichloropropene), caused the adoption in

tomato crops of strategies based on the integration amongchemical and non-chemical

methods (Santos et al., 2006; Bangarwa et al., 2009, 2012;Belova et al., 2013; Qiao et al.,

2015) especially against Cyperus spp. (Gilreath and Santos,2004, 2008; Alves et al., 2013).

Strategies based on integration among herbicides and

plastic mulch (Adcock et al.,

2008) and the use of sulfonylurea herbicides (Hershenhornet al., 1998a,b; Eizenberg

et al., 2003; 2012; Culpepper et al., 2009; Jennings, 2010)were also evaluated to control

Cyperus spp. and other troublesome weeds (e.g. S. nigrum,Phelipanche and Orobanche).

The guidelines for a sound chemical weed control byherbicides in tomatoes crops are

not dissimilar to other crops (Kudsk and Streibig, 2003;Tei and Pannacci, 2016):

• using herbicides with different modes of action andherbicide mixtures in order to reduce the risk of theevolution of herbicide-resistant weeds and the reduction ofweed community biodiversity;

• applying, if available, decision-making procedures basedon weed competition thresholds;

• optimizing herbicide dose in function to key weed species(e.g. Onofri et al., 1995; Kudsk, 2008) and weed stages(e.g. with application of low dosage system; Mullen etal., 2001);

• using active ingredients with low environmental impact(Onofri et al., 1998);

• preferring post-emergence or post-transplantingapplications that allow more accurate weed scouting, and,as a consequence, a more correct choice of foliarabsorbedherbicides that usually show a lower environmental risk dueto a quicker soil dissipation (Onofri et al., 1998);

• adopting a localized application of the herbicides by rowband application (e.g. Lanini et al., 2014) or dripirrigation (e.g. Dittmar et al., 2012b; Jeffries et al.,2014);

• developing, improving and using site-specific weedmanagement (SSWM) (Christensen et al., 2009).

10 Case studies

The following three case studies illustrate how research

has been used to improve tomato

cultivation in practice. In the first two examples, wepresent researches carried out

from field experiments that indicate IWM on individual weedspecies of tomato. In the

third example, we examine the long-term effects of varioustactical options on a mixed

community of weed species.

10.1 Case study 1 – Management of Solanum nigrum L.

Solanum nigrum and related species (Edmonds and Chweya,1997) are key weeds in all

the growing areas of processing tomato throughout the worldwhere the infestations show

high competitive ability and can cause high yield losses(Alex, 1964; Maillet and Abdel

Fatah, 1983; Damato and Montemurro, 1986; Weaver et al.,1987; Jacquard and Abdel

Fatah, 1988; Caussanel et al., 1989, 1990; Perez andMasiunas, 1990; McGiffen et al.,

1992; Bucklew et al., 2006).

S. nigrum is characterized by a long period of emergence(Holm et al., 1977; Rogers

and Ogg, 1981) that forces the farmers to take repeatedweed control measures (Weaver

et al., 1987; Caussanel et al., 1990; Branthôme, 1990,1994; Zaragoza et al., 1994) with a

high percentage of herbicide use in conventional farmingsystems.

Pre- and post-emergence/transplanting herbicides authorizedfor use in tomato are

labelled for controlling S. nigrum in both direct-seededand transplanted processing

tomato (e.g. Tei et al., 2003; Ronchi and da Silva, 2010;Lanini et al., 2014; Freeman

et al., 2015), but the management of S. nigrum is extremelydifficult because of continuous

fluxes of weed germination and emergence, incompleteherbicide activity and sometimes

low selectivity.

Moreover, the efficacy of post-emergence orpost-transplanting application is affected

by the weed growth stages: herbicides have to be applied atvery early weed growth

stages, that is, cotyledon – 1st leaf stages; laterapplication shows no efficacy.

So, a low post-transplanting split-rates strategy(Branthôme, 1994; Onofri et al., 1995;

Mullen et al., 1997, 1999, 2001) was developed andrecommended in order to increase

efficacy and selectivity and reduce the active ingredientsapplied in the soil–plant system.

Therefore, IWM of S. nigrum (Montemurro and Preziosa, 2000;Tei et al., 2003; Lanini

et al., 2014) should be based on: (1) adoption of adequatecrop rotation to reduce the

S. nigrum abundance (es. Vergniaud et al., 1984); (2) weedcontrol in the previous crops

where it is easier; (3) early soil preparation and chemicalor physical control of first

emergence fluxes of Solanum before tomato planting; (4)preferring transplanted than

direct-seeded tomatoes in order to increase cropcompetitive ability against the weed

and have a large difference of growth stages between cropand weeds (i.e. increase of

weed control selectivity); (5) row localization ofeffective residual herbicides at planting

integrated by inter-row mechanical control and/or by splitlow-dose treatments with

effective active ingredients against S. nigrum at veryearly growth stage (cotyledons).

10.2 Case study 2 – Management of Phelipanche andOrobanche spp.

Phelipanche and Orobanche species (broomrapes) are rootholoparasitic plants that cause

severe damage to economically important crops; inparticular, Phelipanche aegyptiaca,

Phelipanche ramosa (syn. O. ramosa) and Orobanche cernuaLoefl. are extremely

troublesome weeds in tomato crops (Joel et al., 2007).

A number of researches were carried out in the past decadesto evaluate different

indirect (e.g. sanitation, trap crops, resistant cultivarselection …) and direct measures

(e.g. soil solarization, soil treatment with fumigants,manual weeding, biological control,

selective herbicides …) to manage parasite soil seedbankand to prevent damage caused

by weeds, but no single practical method controlled themeffectively (Goldwasser and

Kleifeld, 2004).

So, only an integrated management approach is deemed themost feasible way to

control Phelipanche aegyptiaca in tomato (Hershenhorn etal., 2009; Rubiales et al.,

2009b). Hershenhorn et al. (2009) in their review concludedthat

1 quaternary ammonium compound

didecyl-dimethyl-ammonium-bromide (DDAB) have been foundeffective in Phelipanche and Orobanche spp. seederadication for disinfection of agricultural equipment;

2 biological control (i.e. easy-to-use commercial fungalproduct) and selection of broomrape-resistant tomatovarieties are very promising measures, but at present thefeasibility of these control methods is still low, althougha continuous effort should be invested in developing them;

3 on the basis of many field researches conducted over thelast ten years, the most feasible way to manage broomrapesin tomato is the integration of the application ofherbicides (i.e. sulfosulfuron) through the soil (i.e.herbigation) and foliar systemic herbicides (i.e. imazapicand imazamox) on tomato foliage followed by sprinklerirrigation. Herbigation (i.e. delivery of herbicidesthrough drip irrigation) and presoil herbigation (i.e.herbigation before crop planting) with sulfonylureaherbicides should saturate the soil with herbicidesolution and so control germinating seeds and youngattachments. The control of germinating broomrape seeds andyoung attachments is based on direct exposure of theparasitic weeds to the herbicide solution in the soil orthrough the tomato plant that absorbs the herbicide fromthe soil solution and then translocates it to the attachedparasites. Since imazapic and imazamox applied to tomatocanopy injure the flowers and fruit buds, herbicidesshould be applied after the termination of the fruit set(i.e. 45 days before harvest or later). A DSS termedPICKIT for P. aegyptiaca control in processing tomato wasdeveloped to optimize the herbicide rate and application infunction of crop and weed growth and development.

10.3 Case study 3 – Management of a mixed weed community

Hillger et al. (2006a) carried out a study to classify by amultivariate statistical analysis 59

Indiana fields of tomato, both conventional and organic, inrelation to the management

system. The analysis identified five management systems,three systems for fresh market

tomatoes and two for processing tomato, based primarily ondifferences in hours spent

hand weeding, use of plastic mulch, irrigation, row spacingand whether tomatoes were

staked. The study suggests that conventional tomato growersin Indiana who are interested

in transitioning to organic production may face substantialhurdles related to weed

management: irrigated organic fresh market tomato grouprequired many more hours

of hand weeding to produce tomatoes than fields in theother groups of irrigated mixed

fresh market, irrigated processing, rain-fed mixed freshmarket and rain-fed processing

tomatoes.

The same authors in another paper (Hillger et al., 2006b),connected with the previous

one, reported that weed communities were strongly affectedby management systems:

Portulaca oleracea L. (common purslane) was stronglyassociated with the rain-fed

mixed fresh-market system, while Echinochloa crus-galli(L.) Beauv. (barnyardgrass),

Eleusine indica (L.) Gaertn. (goosegrass), Setaria viridis(L.) Beauv. (green foxtail) and

Cyperus esculentus L. (yellow nutsedge) were associatedwith the irrigated organic fresh

market system. In the fresh-market systems, after weedmanagement practices aimed

at respecting CPWC, weed densities at end of growing seasonranged from 23 to 30

plants m –2 while in processing tomato ranged from 7 to 13plants m –2 ; since weed species

showed that high seed production, weed soil seedbank andweed problems would be

significantly augmented in subsequent crops. For thisreason, the authors pointed out

that some Indiana tomato growers include more competitivecrops, such as soybeans, in

the crop rotations to compensate for the increase of thesoil seedbank during the tomato

crop cycle.

Mayen et al. (2008), starting from results obtained byHillger et al. (2006a,b) and from

the ‘NST’ approach proposed by Norris (1999), appliedcontrasted threshold strategies in

which weeds were either controlled for four to six weeks(i.e. CPWC) or throughout the

growing season (i.e. NST). Weed seed banks did notsignificantly change in the NST plots

whereas they increased substantially in CPWC plots mainlydue to an insufficient control of

a late-emerging giant foxtail (Setaria faberi Herrm.); incontrast, weed seed bank densities

decreased following soybeans in CPWC plots. A greatersuppression of giant foxtail by

the soybean canopy and higher efficacy of weed controlmeasures applied in soybeans

explained the presence of lower seed banks and emergedweeds recorded in soybeans in

comparison with tomatoes.

These studies highlight the limit of weed thresholds basedon yield losses and the

need to develop a long-term IWM strategy to prevent largeincreases in the weed seed

bank within the whole crop rotation (Buhler et al., 1997;Gallandt, 2006; Anderson, 2005;

Graziani et al., 2012; Colbach et al., 2014; Storkey etal., 2015).

11 Summary and future trends

Research can contribute to enhanced and sustainable cropproduction through improved

knowledge in each of the following steps of the IWM:

1 collecting information by survey about key weeds andspecies that are becoming an increasing problem in eachfarm/country;

2 deepening scientific knowledge on multifactorialinteraction in weed population management by the differentagronomic practices applied;

3 defining reliable weed density and duration thresholds;

4 building up reliable and friendly models and/or DSS;

5 improving efficacy and selectivity of direct control;

6 improving environmental sustainability of chemical weedcontrol;

7 improving SSWM methods.

A number of papers have focused on the future weed scienceresearch agenda (e.g. Kropff

and Walter, 2000; Kropff et al., 2008;Fernandez-Quintanilla et al., 2008; Bakar, 2010;

Hurle et al., 2012) in a changing agricultural scenario.

Authors confirmed the importance of improving the basicknowledge on weed biology,

ecology and population dynamics, and weed–crop competitionrelationships, but they

chiefly emphasized and discussed the need for elaboratingadvanced (i) long-term weed

management strategies, (ii) DSS to aid farmers in weedcontrol, (iii) SSWM systems to

optimize the use of direct weed control measures and (iv)selection of crops resistant to

herbicides and parasitic weeds by using molecular biology

tools. Bakar (2010) remarked

that many of these research aspects are knowledge-baseddecision-support strategies and

system-approach-based decisions.

In this chapter, we have already discussed many of theabove-mentioned research

aspects that are crucial components of IWM; in thisparagraph, we synthetically point out

two developments in weed science that are deemed to alsohave a significant evolution

in the future: SSWM methods and the new tools offered bymolecular biology and

genomics.

SSWM methods. It has been extensively documented that theweeds are not evenly

distributed in the fields, but on the contrary, theirspatial distribution is aggregated at

forming random patches (e.g. Marshall, 1988; VanGroenendael, 1988; Hughes, 1990) not

stable in location (Heijting et al., 2007). Cardina et al.(1997) focused his attention on the

consequences of the heterogeneous weed spatial distributionfor weed scouting, yield

loss prediction, weed competition thresholds determinationand weed management.

SSWM methods were developed by taking into account thespatial heterogeneity of

weeds to maximize the chances of successfully controllingweeds by using machinery

or equipment embedded with new technologies for sensoring,physical-weeding and

spraying (Christensen et al., 2009).

SSWM is based on three main key components:

1 remote (i.e. airborne-, satellite- and unmanned-basedplatforms) and/or proximal (i.e. on-ground sensor andcameras) weed monitoring system to detect and map weeds(e.g. for general aspects: Brown and Noble, 2005; Gee etal., 2008; Lopez-Granados, 2011; Singh et al., 2011; forspecific application in tomato: Slaughter et al., 2004; Sunet al., 2010; Zhang and Slaughter, 2011);

2 a DSS, usually based on competition models (e.g. Benjaminand Park, 2007; Grundy et al., 2005; Gutjahr and Gerhards,2010), to determine weed thresholds and concomitant weedcontrol measures (Longchamps et al., 2014);

3 actuators for making treatments (e.g. Christensen et al.,2009) for chemical (e.g. Giles et al., 2004; Weis et al.,2011), mechanical (e.g. Perez-Ruiz et al., 2012; Gobor etal., 2013) or other physical weed control measures.

Developments in SSWM were obtained with autonomous roboticweed control systems

(Lee et al., 1999; Slaughter et al., 2008; Perez-Ruiz etal., 2014; Melander et al., 2015) that

embedded a row guidance system (usually by an automaticreal-time kinematic global

positioning system, RTK-GPS), a machine vision recognitionof plant species, a precision

in-row weed control method (mechanical, thermal, electricalor chemical) for robotic

actuation and a GPS mapping system.

Molecular biology and genomics. In the last three decades,the application of

biotechnologies in agriculture has shown a stunningdevelopment mainly in crop breeding

programmes (Moose and Mumm, 2008). Breeding andcommercialization of Genetically

Modified (GM) insect-resistant and herbicide-tolerant crops(as soybean, maize, cotton,

rice, canola, potato, and alfalfa) have been the goal of

private and public researches, but

they have also led to public concerns due to human health(Dona and Arvanitoyannis,

2009) and environment risks (Duke, 2011).

However, molecular biology and genomics is deemed toimprove knowledge in weed

science and to yield novel weed management strategies notnecessarily based on

herbicides (e.g. Gressel, 2002; Duke, 2003; Basu et al.,2004; Lee and Tranel, 2008; Tranel

and Horvath, 2009; Westwood et al., 2012; Mortensen et al.,2012); the most potential and

promising use of biotechnologies in weed science can besummarized as follows:

• studying the genetic basis of gene expression ofweediness, weed behaviour and population dynamics;

• studying the mechanisms and evolution of herbicideresistance in weed populations;

• enhancing the natural allelopathic potential of a crop oreven to introduce allelopathy into a crop;

• improving our understanding on target sites for herbicideaction, evolution of herbicide resistance and aiding inthe identification of novel herbicide targets andstrategies (as trans-specific gene silencing);

• developing pathogens more virulent to the weeds to beused for effective bioherbicides;

• identification of weed genes that could improve cropyields.

As an example, Aly (2012) reviewed the use of biotechnologyfor studying Phelipanche

aegyptiaca virulence, host-resistance mechanisms andmanagement. Moreover, he

presented two new approaches for the development ofherbicide-resistant crops based

on (i) the inducible expression of cecropin (i.e.polypeptide produced by the plant that

inhibits broomrape seed germination and radicle elongation)in tomato transgenic plants

and (ii) the silencing of a key-target gene in the parasite.

Finally, biotechnology can also be used for improving thefeasibility of SSWM: Lati et al.

(2013) reported an innovative approach that combinesadvances in genetic engineering

and image-processing methods to detect weeds anddistinguish them from tomato crop

plants by manipulating the crop’s leaf colour (i.e. usingGM tomato which expresses a

purple leaf colour).


Books

Weed Science and Research, P. E. Hatcher and R. J.Froud-Williams (Eds), Wiley & Sons, New York, 2016 (inpress).

Weed Biology and Management, Inderjit (Ed.), KluwerAcademic Publishers, The Netherlands, 2003, p. 553.

Non-Chemical Weed Management: Principles, Concepts andTechnology, M. K. Upadhyaya and R. E. Blackshaw (Eds),CABI, Wallingford, Oxon, UK, 2007, p. 239.

Weed–Crop Competition. A Review, R. L. Zimdahl (Ed.), 2ndedition, Blackwell Publishing Professional, Ames, IA, USA,2004, p. 220.

Key societies

International Weed Science Society, IWSS – www.iwss.info.

European Weed Research Society, EWRS – www.ewrs.org.

Weed Science Society of America, WSSA – www.wssa.net.

International Society for Horticultural Science, ISHS –www.ishs.org.

Key journals

Weed Research: The Official Journal of EWRS –http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291365-3180.

Weed Science: An Official Journal of WSSA –http://wssajournals.org/loi/wees.

Weed Technology: An Official Journal of WSSA –http://wssajournals.org/loi/wete.

Crop Protection: The Official Journal of the InternationalAssociation for the Plant Protection – http://www.journals.elsevier.com/crop-protection/.

Acta Horticulturae: Official Proceedings of ISHS Symposia,Congresses and Conferences – http:// www.actahort.org.

Key conferences

EWRS Symposia and Working Group Workshops: the EWRSSymposia series have a 2–3–3 year periodicity whileWorking Group Workshops commonly do not have anyperiodicity. Free publications of Symposia and Workshopsare available at http://www.ewrs.org/publications.asp.

AWSS Meetings: The Society’s annual meeting is usuallyduring the first full week of February and is held at adifferent location each year in the United States or inCanada. Free meeting abstracts are available athttp://wssa.net/meeting/meeting-abstracts/.

International Weed Science Congress (IWSC): it is organisedevery 4 years by the IWSS. Proceedings of the meetings areavailable at http://www.iwss.info/proceedings.php?AM1.

ISHS Symposia, Congresses and Conferences: Proceedings ofthe Symposia, Congresses and Conferences organised by themany ISHS Sections, Commissions and Working Groups arepublished in Acta Horticulturae series available athttp://www.actahort.org/.

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